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Phantom sensation: Threshold and quality indicators of a tactile illusion of motion Displays (IF 4.3) Pub Date : 2024-03-13 Byron Remache-Vinueza, Andrés Trujillo-León, Fernando Vidal-Verdú
Utilizing a randomized, blind, controlled experiment, and the ascending method of limits, we determined the minimum amplitude of motion at which individuals perceive a tactile illusion called moving phantom sensation, the perceived level of clarity and continuity of motion. Implementing tactile illusions in virtual/augmented reality, sensory substitution systems, and other human–computer interaction
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Modeling the carrier density in the exciton formation zone of organic light-emitting diode under high current injection Displays (IF 4.3) Pub Date : 2024-03-11 Dashan Qin
The carrier density in exciton formation zone is the electrical parameter most relevant to the stability of organic light-emitting diode: the decrease of carrier density improves the device stability. Here, based on the general mode of carrier device lifetimes, the carrier densities in the exciton formation zone of organic light-emitting diode have been calculated at current densities () ≥ 2.0 kA cm
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The influence of signal hue and background music pitch on vigilance Displays (IF 4.3) Pub Date : 2024-03-11 Jinghan Wang, Yanqun Huang, Xueqin Huang, Junyu Yang, Jutao Li
Humans generally display vigilance decrement during sustained cognitive workloads, while visual and auditory stimuli have been shown to elicit arousal, which influences the level of user vigilance. This study explored the effects of hue and background music pitch on user vigilance. Thirty-five participants performed a 10-min Psychomotor Vigilance Test with background music playing. Three hue conditions
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Human pose estimation in crowded scenes using Keypoint Likelihood Variance Reduction Displays (IF 4.3) Pub Date : 2024-03-11 Longsheng Wei, Xuefu Yu, Zhiheng Liu
Human pose estimation can be applied to many computer vision tasks, such as human–computer interaction, motion recognition, and action detection. However, few previous methods focused on the pose estimation problem in crowded scenes. Connection-based bottom-up approaches are the main pipelines in multi-person pose estimation. Keypoint detection, connection detection and pose assembly are the main processes
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Video-based craniomaxillofacial disease screening system Displays (IF 4.3) Pub Date : 2024-02-28 Kaixun Zhang, Yuhang Men, Yiqiao Shi, Jiajie Chen, Jing Han, Menghan Hu, Jiannan Liu
Craniomaxillofacial disease, which is common all over the world, is difficult to screen at early stage. It will probably affect the patient’ facial appearance once someone suffers from it. This paper introduces an integrated system that is composed of data collection, three-dimensional reconstruction, and disease screening, facilitating timely detection of craniomaxillofacial diseases. With an expanding
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The effect of short-form video content, speed, and proportion on visual attention and subjective perception in online food delivery menu interfaces Displays (IF 4.3) Pub Date : 2024-02-24 Mengyao Qi, Kenta Ono, Lujin Mao, Makoto Watanabe, Jinghua Huang
Given the rising popularity of utilizing short-form videos as visual cues, employing short-form videos to showcase food visual information in online food delivery menu interfaces could be a promising approach. However, it remains unclear about the effect of short-form video attributes on visual attention and perception of online food delivery consumers. In an experimental study with 36 participants
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A contrastive learning based unsupervised multi-view stereo with multi-stage self-training strategy Displays (IF 4.3) Pub Date : 2024-02-24 Zihang Wang, Haonan Luo, Xiang Wang, Jin Zheng, Xin Ning, Xiao Bai
Recent years, unsupervised multi-view stereo (MVS) methods have achieved excellent success that can produce comparable results to earlier supervised work. However, as unsupervised MVS uses image reconstruction as pretext task, it faces two vital drawbacks: RGB value, which is the measurement of image, is not robust enough across views due to complicated environment like lighting conditions and reconstruction
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RTHEN: Unsupervised deep homography estimation based on dynamic attention for repetitive texture image stitching Displays (IF 4.3) Pub Date : 2024-02-21 Ni Yan, Yupeng Mei, Tian Yang, Huihui Yu, Yingyi Chen
Homography estimation is regarded as one of the key challenges in image alignment, where the goal is to estimate the projective transformation between two images on the same plane. Unsupervised learning methods are gradually becoming popular due to their excellent performance and lack of need for labeled data. However, in regional scenes with repeated textures, there may be ambiguity in the correspondence
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Effects of color scheme and visual fatigue on visual search performance and perceptions under vibration conditions Displays (IF 4.3) Pub Date : 2024-02-17 Da Tao, Xinyuan Ren, Kaifeng Liu, Qian Mao, Jian Cai, Hailiang Wang
Visual search represents one of the most encountered human–computer interaction tasks. However, the effect of visual fatigue on visual search, especially in conditions involving vibrations, remains largely known. The objective of this study was to assess the effects of color scheme and visual fatigue on visual search performance and perceptions in different vibration conditions. We conducted an experiment
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The role of lifestyle factors, biological sex, and racial identity for (visually induced) motion sickness susceptibility: Insights from an online survey Displays (IF 4.3) Pub Date : 2024-02-16 Narmada Umatheva, Frank A. Russo, Behrang Keshavarz
Motion sickness (MS) and visually induced motion sickness (VIMS) are common side-effects when travelling or when using visual devices, respectively. A variety of individual factors may determine one’s susceptibility to MS/VIMS. Here, the role of lifestyle factors including video-game usage, physical activity, diet, and substance use on self-reported susceptibility to MS/VIMS was investigated. Additionally
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Visually guided movement in virtual reality is tolerant of the vergence-accommodation conflict Displays (IF 4.3) Pub Date : 2024-02-16 Ken McAnally, Guy Wallis, Philip Grove
Stereoscopic virtual reality (VR) headsets display vergence cues to object distance but present images at a fixed focus, resulting in a vergence-accommodation conflict (VAC). This study examined the effects of introducing or reducing the VAC with optical lenses in a targeted reaching task implemented in both VR and the real world. Contrary to previous reports of reduced visual performance and fatigue
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Effectiveness and visual performance assessment of anti-peeping films Displays (IF 4.3) Pub Date : 2024-02-16 Wenqian Xu, Qi Yao, Peiyu Wu, Rongjun Zhang, Wei Zhu, Pengfei Li, Leimin Bao
Some private information inevitably becomes more visible when using wide-angle electronic devices in public places. Thus, some people use anti-peeping films to achieve privacy protection. To examine the effectiveness and its influence on the visual performance of the anti-peeping film, we investigated the color gamut, luminance, contrast ratio, Bhattacharyya coefficient and structural similarity characteristics
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Contrastive adaptive frequency decomposition network guided by haze discrimination for real-world image dehazing Displays (IF 4.3) Pub Date : 2024-02-15 Yaozong Mo, Chaofeng Li
Recent unsupervised image dehazing methods used unpaired real-world training data for enhancing generalization on real-world scenes. However, these methods often require dehazing and rehazing cycles with auxiliary networks for training, resulting in high computational costs and extended training time. In this work, we propose an unsupervised dehazing framework called Contrastive Adaptive Frequency
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Effects of anthropomorphic design on comprehension of self-monitoring test results: Integrating evidence of eye-tracking and event-related potential Displays (IF 4.3) Pub Date : 2024-02-12 Pengbo Su, Kaifeng Liu
To investigate the effects of anthropomorphism design on individuals’ comprehension of self-monitoring test results. In addition, we employed eye-tracking and event-related potential techniques to explore the underlying mechanisms. A within-group design was employed with presentation format (black-and-white neutral design, black-and-white anthropomorphic design, and colored anthropomorphic design)
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A dynamic detection and data association method based on probabilistic models for visual SLAM Displays (IF 4.3) Pub Date : 2024-02-10 Jianbo Zhang, Liang Yuan, Teng Ran, Song Peng, Qing Tao, Wendong Xiao, Jianping Cui
Visual Simultaneous Localization and Mapping (VSLAM) is a critical foundation in mobile robotics and augmented reality (AR). However, VSLAM faces challenges in dynamic environments since both the camera and the object are in motion, which contradicts the classical static scene assumption. Generally, multi-view geometry is employed for static features to estimate camera pose and reconstruct environment
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The effects of representation of industrial icons on visual search performance Displays (IF 4.3) Pub Date : 2024-01-29 Jiang Shao, Yuhan Zhan, Hui Zhu, Mingming Zhang, Lang Qin, Shangxin Tian, Hongwei Qi
With innovations in intelligent manufacturing technology and the enhancement of intelligent manufacturing systems, the quantity of information held and transmitted by interactive interfaces has increased significantly, which also increases the cognitive load on the operators. As a component of an interactive interface, the icon has the vital mission of communicating semantics. The eye-movement experiments
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Automatic quantitative intelligent assessment of neonatal general movements with video tracking Displays (IF 4.3) Pub Date : 2024-02-02 Xinrui Huang, Chunling Huang, Wang Yin, Hesong Huang, Zhuoheng Xie, Yuchuan Huang, Meining Chen, Xinyue Fan, Xiaoteng Shang, Zeyu Peng, You Wan, Tongyan Han, Ming Yi
General movement (GM) assessment (GMA) is an internationally recognised tool for the early screening and diagnosis of neurodevelopmental abnormalities in high-risk infants. Traditional GMA requires multiple internationally certified doctors, which is subjective and time-consuming and therefore limits its widespread use, especially among neonates. Quantifying and accelerating GMA can reduce artificial
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Improving Braille–Chinese translation with jointly trained and pre-trained language models Displays (IF 4.3) Pub Date : 2024-02-01 Tianyuan Huang, Wei Su, Lei Liu, Chuan Cai, Hailong Yu, Yongna Yuan
The education of visually impaired children remains a focal topic, and the implementation of Braille–Chinese translation can facilitate improved understanding and learning of Braille for these children. Braille–Chinese translation refers to the conversion of Braille text into Chinese characters. Owing to the scarcity of Braille–Chinese parallel corpora, achieving Braille–Chinese translation with limited
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Towards better video services: An EEG-based interpretable model for functional quality of experience evaluation Displays (IF 4.3) Pub Date : 2024-01-29 Yifan Niu, Kexin Di, Gangyan Zeng, Tao Wei, Yuan Zhang, Xia Wu
Since emerging video services can provide emotional and social value to users, the setting of their functional parameters directly affects human cognitive and affective states, further influencing video services’ quality of experience (QoE), which we call functional QoE (fQoE). FQoE is highly dependent on human subjective perceptions and the reasons for its generation are important for service providers
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DSSO-YOLO: A fast detection model for densely stacked small object Displays (IF 4.3) Pub Date : 2024-01-28 Zheng Zhang, Liangchen Liu, Xunyi Zhao, Lijun Zhang, Jun Wu, Yan Zhang, Zhenghao Li
Visual detection for densely stacked small object (DSSO) has a wide range of applications in the construction, logistics, and import/export industries. Take the construction industry as an example, intelligent rebar counting, can considerably improve the management efficiency in sales, delivery and inventory management. It can also effectively prevent acts such as supervisory theft. However, current
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Prediction model for indoor light environment brightness based on image metrics Displays (IF 4.3) Pub Date : 2024-01-28 Chao Ruan, Li Zhou, Liangzhuang Wei, Wei Xu, Yandan Lin
Currently, rapid progress in display technology and optical simulation software has enabled the visualization of lighting design, which can provide abundant visual information. However, renderings only allow designers to subjectively judge whether the lighting layout and optical parameters are reasonable. So we want to combine the rendered images and photometric data in the process of optical simulations
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Investigating visual determinants of visuomotor performance in virtual reality Displays (IF 4.3) Pub Date : 2024-01-22 Ken McAnally, Guy Wallis, Philip Grove
We report the relative efficiency of visually guided movement in virtual reality (VR) compared to that in the real world using a standardised visuomotor task based on Fitts’ tapping. Haptic cues were veridical across both displays to ensure that any differences in performance could be attributed to characteristics of the visual display. The presence of binocular cues, and of monocular surface texture
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ARD-SLAM: Accurate and robust dynamic SLAM using dynamic object identification and improved multi-view geometrical approaches Displays (IF 4.3) Pub Date : 2024-01-23 Qamar Ul Islam, Haidi Ibrahim, Pan Kok Chin, Kevin Lim, Mohd Zaid Abdullah, Fatemeh Khozaei
In the evolving landscape of autonomous navigation, traditional Visual Simultaneous Localization and Mapping (SLAM) systems often encounter challenges in dynamic environments, primarily due to their reliance on assumptions of static surroundings. In response to these limitations, we introduce ARD-SLAM, a groundbreaking approach to dynamic SLAM that innovatively combines global dense optical tracking
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RAWIW: RAW Image Watermarking robust to ISP pipeline Displays (IF 4.3) Pub Date : 2024-01-24 Kang Fu, Xiaohong Liu, Jun Jia, Zicheng Zhang, Yicong Peng, Jia Wang
Invisible image watermarking is essential for image copyright protection. Compared to RGB images, RAW format images use a higher dynamic range to capture the radiometric characteristics of the camera sensor, providing greater flexibility in post-processing and retouching. RAW images are considered the original format for distribution and image production, thus requiring copyright protection. Existing
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Charge generation layer with Yb assistant interlayer for tandem organic light-emitting diodes Displays (IF 4.3) Pub Date : 2024-01-19 Kanghoon Kim, Jae-In Yoo, Sung-Cheon Kang, Hyo-Bin Kim, Eun-young Choi, Sundararajan Parani, Jang-Kun Song
Tandem organic light-emitting diode (OLED) devices require an efficient charge generation layer (CGL) between two stacked OLED units. In this study, a CGL with an Yb assistant interlayer was fabricated and investigated. The optical transmittance and charge generation performances of the CGLs were analyzed with respect to the Yb thickness. The best result was obtained at a Yb thickness of 3 nm, at which
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A convolutional neural network-based rate control algorithm for VVC intra coding Displays (IF 4.3) Pub Date : 2024-01-19 Jiafeng Wang, Xiwu Shang, Xiaoli Zhao, Yuhuai Zhang
The Versatile Video Coding (VVC) has shown significant improvements in Rate-Distortion (R-D) performance compared to its predecessor, High Efficiency Video Coding (HEVC). However, it still encounters several challenges. One of these challenges is the efficient allocation of bits among all Coding Tree Units (CTUs). Additionally, there is a lack of prior information for intra-frame coding, particularly
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ReverseGAN: An intelligent reverse generative adversarial networks system for complex image captioning generation Displays (IF 4.3) Pub Date : 2024-01-19 Guoxiang Tong, Wei Shao, Yueyang Li
Towards the inclusion of complex semantic relational images, we propose an intelligent Reverse Generative Adversarial Network (ReverseGAN) with generative task guidance to build an image caption system. The system utilizes regenerated images to learn the concept of image caption generation, using a generative adversarial network as the overall framework of the model. The generative network uses a graph
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CHDNet: A lightweight weakly supervised segmentation network for lung CT image Displays (IF 4.3) Pub Date : 2024-01-19 Fangfang Lu, Tianxiang Liu, Ting Zhang, Bei Jin, Weiyan Gu
Deep learning methods have ushered in an unprecedented transformation in medical image segmentation by automating the segmentation of computed tomography (CT) slices. However, challenges persist in the application of these deep learning methods, including models with a high number of training parameters which hinder their clinical deployment and practical use. Furthermore, acquiring a large volume
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Ai-aided diagnosis of oral X-ray images of periapical films based on deep learning Displays (IF 4.3) Pub Date : 2024-01-11 Lifeng Gao, Tongkai Xu, Meiyu Liu, Jialin Jin, Li Peng, Xiaoting Zhao, Jiaqing Li, Mengting Yang, Suying Li, Sheng Liang
Oral X-ray images provide a useful technical means by which dentists examine teeth for dental problems, but the diagnostic process is defective due to its over-reliance on dentists’ subjective judgments, lack of objective criteria, etc. In this context, this study examined the AI-aided diagnosis of periapical films based on deep learning..Based on YOLOv7-X, a YOLO-DENTAL network architecture was used
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WHRIME: A weight-based recursive hierarchical RIME optimizer for breast cancer histopathology image segmentation Displays (IF 4.3) Pub Date : 2024-01-11 Jie Xing, Ali Asghar Heidari, Huiling Chen, Hanli Zhao
In medical image processing, multi-threshold image segmentation has been challenging, as selecting appropriate thresholds is crucial for distinguishing different structures within an image, especially when dealing with breast cancer images. Breast cancer images are complex with multiple tissue types, which pose challenges to precise diagnosis. A weight-based recursive hierarchical bootstrapping rime
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A directionally illuminated pixel-selective flickering-free autostereoscopic display Displays (IF 4.3) Pub Date : 2024-01-10 Yong He, Xuehao Chen, Guangyong Zhang, Yunjia Fan, Xingbin Liu, Dongyan Deng, Zhongbo Yan, Haowen Liang, Jianying Zhou
A directionally illuminated pixel-selective flickering-free autostereoscopic display is proposed and demonstrated. The system consists of the U-shaped backlight, the mix-grooves cylindrical Fresnel lens array, a light shaping diffuser film, and a liquid crystal display with a directional light splitting element. Simulation is applied to obtain the crosstalk and the illuminance distribution at each
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Effect of rough screen on speckle suppression by wavelength and angle diversity in laser projection systems Displays (IF 4.3) Pub Date : 2024-01-09 Yuantong Chen, Linxiao Deng, Binghui Yao, Yuhua Yang, Liquan Zhu, Ting Li, Lixin Xu, Chun Gu
In speckle suppression research, screens play a critical role in formation of speckle. This paper examines screen speckle using diverse light sources and screens of varying roughness. Our findings demonstrate that speckle suppression by screens is the key reason wavelength and angle diversities are not mutually independent in existing literature. Different from the theory, our experiments reveal that
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Lightweight and fast visual detection method for 3C assembly Displays (IF 4.3) Pub Date : 2024-01-02 Wenbai Chen, Genjian Yang, Bo Zhang, Jingchen Li, Yiqun Wang, Haobin Shi
In the context of 3C assembly scenarios, characterized by numerous semi-flexible, heterogeneous, and small slender targets, traditional target detection algorithms face significant challenges such as low accuracy, weak generalization, large model sizes, and slow inference speeds. To address these issues, this study introduces an enhanced method based on the YOLOv5 model, named YOLOv5-GTB. This method
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Applications of liquid crystal planer optical elements based on photoalignment technology in display and photonic devices Displays (IF 4.3) Pub Date : 2024-01-05 Fangfang Chen, Jihong Zheng, Chenchen Xing, Jingxin Sang, Tong Shen
Liquid crystal (LC) planar optical elements (POEs) based on photoalignment technology have emerged as a promising approach to manipulating light in various ways. Owing to the high diffraction efficiency, polarization sensitive, and simple fabrication process, LC POEs have found enormous applications in display and photonic devices. In this review, we analyze the Pancharatnam-Berry (PB) phase, polarization
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Underwater image classification based on image enhancement and information quality evaluation Displays (IF 4.3) Pub Date : 2024-01-04 Shuai Xiao, Xiaotong Shen, Zhuo Zhang, Jiabao Wen, Meng Xi, Jiachen Yang
Underwater target imaging is widely used in oceans, rivers and lakes detection fields, but due to the existence of water on light absorption scattering attenuation effect, the diffraction limit of imaging system, aberration distortion and underwater turbulence, underwater images has serious degradation, mainly manifested in noise, fuzzy and low resolution, etc. In recent years, some scholars have started
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Advances, challenges and prospects of visible fiber lasers in display technologies Displays (IF 4.3) Pub Date : 2023-12-31 Wensong Li, Wei Mi, Lu-Jian Chen
Especially for displays, visible-wavelength lasers are in high demand for a wide range of applications. Active research and development have been devoted to laser-based displays over the past six decades, but the technology’s commercial viability has been limited primarily by the high cost and bulk of laser sources. Owing to their reliability, cost-effectivity, and high efficiency, fiber lasers are
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Shape classification using a new shape descriptor and multi-view learning Displays (IF 4.3) Pub Date : 2023-12-30 Davar Giveki, Mohammad Ali Soltanshahi, Homayoun Rastegar
Shape classification is considered as a vital task in solving many computer vision problems. Different factors such as affine transformations, scaling, rotations, variation in perspective, noise and occlusion have made the shape classification problem to be a hard problem. This work investigates a new shape descriptor that extracts different features from each boundary pixel. This makes it to be more
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Efficient multi-branch dynamic fusion network for super-resolution of industrial component image Displays (IF 4.3) Pub Date : 2023-12-30 Guanqiang Wang, Mingsong Chen, Y.C. Lin, Xianhua Tan, Chizhou Zhang, Wenxin Yao, Baihui Gao, Kai Li, Zehao Li, Weidong Zeng
This work aims to promote the application of a high-performance super-resolution (SR) method in industry. Considering the lack of industrial datasets to evaluate performance, an industrial image SR dataset called WCI110 is first established, comprising 110 typical welding component images with 2040 × 1524 pixels. Subsequently, a parallel fusion structure of CNN and Transformer (FPFCT) is designed to
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Attentional Feature Erase: Towards task-wise transferable adversarial attack on cloud vision APIs Displays (IF 4.3) Pub Date : 2023-12-30 Bo Cheng, Yantao Lu, Yilan Li, Tao You, Peng Zhang
Recent works have shown that adversarial examples (AEs) can attack and successfully transfer across various neural networks, highlighting the potential danger they pose. However, current approaches that focus on task-specific loss functions may not be as effective across different tasks. Additionally, the use of cloud APIs in practice, which often involve combining multiple tasks, also weakens the
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Configuration of a depth-fused 3D pyramid display for volumetric art Displays (IF 4.3) Pub Date : 2023-12-30 Yogi Udjaja, Tomoyoshi Ito, Tomoyoshi Shimobaba
An increasingly indispensable facet of modern communication systems is the establishment of an immersive and lifelike environment that fosters authentic interactions among individuals with diverse vantage points. The cultivation of these organic interconnections finds its conduit in the integration of a depth-fused 3D (DFD) display, a pivotal mechanism for engendering a palpable sense of depth perception
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Panoramic radiograph quality assessment: Database and algorithm Displays (IF 4.3) Pub Date : 2023-12-29 Jiaman Lin, Yanning Ma, Wei Lu, Zhiyuan Qu, Zuolin Jin, Jun Zhou
High-quality panoramic radiographs are crucial for providing accurate diagnosis and appropriate treatment to the patients, which have been widely employed in dentist clinic. Unfortunately, panoramic radiographs can be bothered with various distortions during the capture and imaging process, which can further negatively affect the judgment of dentists. Therefore, to deal with the challenge of panoramic
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CODP-1200: An AIGC based benchmark for assisting in child language acquisition Displays (IF 4.3) Pub Date : 2023-12-29 Guannan Leng, Guowei Zhang, Yu-Jie Xiong, Jue Chen
AIGC (Artificial Intelligence Generated Content) is a novel AI technology that encompasses tasks such as text-to-image generation, text-to-text generation, and image-to-text generation. In the process of child language acquisition, some children may face challenges, exhibiting symptoms such as delayed language development, limited vocabulary, and poor expressive ability. To address this issue, the
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The influence of subjective value on mobile payment security warnings: An eye movement study Displays (IF 4.3) Pub Date : 2023-12-27 Yufei Du, Haibo Yang
Payment security has become a vital issue with the popularization of mobile payments among people and in various fields. Warnings are designed to alert users to potential risks but are only effective if users understand them. The current study aims to investigate whether the subjective value of colour formed by experiences influences the effectiveness of mobile payment security warnings. Using eye-tracking
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Two-Stage and Two-Discriminator generative adversarial network for the inpainting of irregularly incomplete iris images Displays (IF 4.3) Pub Date : 2023-12-26 Ying Chen, Liang Xu, Huiling Chen, Yugang Zeng, Shubin Guo, Junkang Deng, Ali Asghar Heidari
Due to the influence of the light source environment during image acquisition or the subject not fully opening their eyes, there are phenomena such as light spot interference, eyelash or eyelid occlusion in the iris area. This will cause the loss of effective iris information, ultimately affecting the success rate of recognition. To address the aforementioned issues, this paper introduces a Two-stage
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An AIGC-empowered methodology to product color matching design Displays (IF 4.3) Pub Date : 2023-12-22 Fan Wu, Shih-Wen Hsiao, Peng Lu
With the emergence of various generative AI applications, artificial intelligence-generated content (AIGC) demonstrates positive potential for design activities. However, few scholars have proposed a practical AIGC-based design methodology. This paper introduces an AIGC-empowered methodology for product color-matching design. ChatGPT generates target imageries describing the design features, and Midjourney
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Exploring the potential of Sm3+-doped Sr2B2O5 phosphors for bridging the amber gap in w-LED application Displays (IF 4.3) Pub Date : 2023-12-22 Isha Charak, M. Manhas, A.K. Bedyal, H.C. Swart, Vinay Kumar
A series of orange-red emitting Sr2(1-x)B2O5:2xSm3+(x = 0.5–3.0 mol%) phosphors have been synthesized via the self-propagating low-cost solution combustion method. The purpose of this study is to address the amber gap in light-emitting diodes (LEDs). X-ray diffraction technique was employed for structural analysis, which reveals the creation of a purely monoclinic phase having space group P21/a. The
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Product color emotional design based on 3D knowledge graph Displays (IF 4.3) Pub Date : 2023-12-22 Man Ding, Mingyu Sun, Shijian Luo
To address the problem of fragmentation, integration difficulties in fuzzy front-end information, and ambiguity in color emotion knowledge representation and conversion within the current product color emotion design stage, this paper proposes a method based on 3D Knowledge Graph. The proposed approach aims to integrate product color emotion design into the “data knowledge + artificial intelligence”
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Physiological characteristics inspired hidden human object detection model Displays (IF 4.3) Pub Date : 2023-12-15 Menghan Hu, Lejing Zhang, Bailiang Zhao, Yunlu Wang, Qingli Li, Lianghui Ding, Yuan Cao
The current target detection algorithms provide the unsatisfactory performance on the task of detecting hidden human targets. In this study, we put forward the physiological characteristics inspired hidden human object detection model considering the spatio-temporal physiological features and their interdependent relationships. The experimental results of homemade hidden human object dataset demonstrate
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A robust training method for object detectors in remote sensing image Displays (IF 4.3) Pub Date : 2023-12-15 Jiehua Lin, Yan Zhao, Shigang Wang, Yu Tang
With the development of convolutional neural networks (CNNs), remote sensing object detection has been made a great improvement. The CNNs-based detectors rely on accurate manually labeled training data. Due to the characteristics of remote sensing images and the professional requirements of annotation, the quality of data annotation is difficult to guarantee, and the labels of data will inevitably
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No-reference quality assessment of underwater image enhancement Displays (IF 4.3) Pub Date : 2023-12-15 Xiao Yi, Qiuping Jiang, Wei Zhou
Due to the attenuation and scattering of light in the water medium, real-world underwater images usually suffer from diverse quality defects, such as color casts, low contrast, and reduced visibility, etc. These quality defects accordingly cause adverse effects on underwater images in practical applications. To tackle the problem, many underwater image enhancement (UIE) techniques have been proposed
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PCTN: Point cloud data transformation network Displays (IF 4.3) Pub Date : 2023-12-15 Guoqi Wang, Long Yu, Shengwei Tian, Huang Zhang, Yazhang Xue, Mengmei Sang, Jing Guo, Xinglin Yu, Shuxiang Si
In point cloud classification tasks, efficiently extracting point cloud data feature has always been a challenging problem. Based on the characteristics of the point cloud data distribution, the point cloud from different parts contains distinct feature information. Therefore, they cannot be treated equally. In this work, we propose a novel method called PCTN, which primarily consists of two modules:
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The influence of human-computer interface on usability and technology acceptance of VR-based shooting training with a comparison with typical shooting range Displays (IF 4.3) Pub Date : 2023-12-17 Andrzej Grabowski, Damian Bereska, Eryka Probierz, Anita Gałuszka
This paper investigates the influence of the human-computer interface on the usability and technology acceptance of VR-based shooting training in comparison to a typical shooting range. We conducted an experiment with 160 active duty State Protection Service officers who performed shooting tasks in real and four different VR environments with different levels of complexity. The results showed that
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Fast scaled cylindrical holography based on scaled convolution Displays (IF 4.3) Pub Date : 2023-12-16 Chao Tan, Jun Wang, Yang Wu, Jie Zhou, Ni Chen
Recently, the 360°display of cylindrical holography has garnered significant attention. However, existing studies have been limited to concentric cylindrical surfaces with equal heights, which restricts the height of the objects. In this paper, a fast scaled cylindrical holography is proposed based on scaled convolution to break this constraint. Firstly, the scale cylindrical diffraction is derived
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A brain-inspired quality assessment model for sonar image super-resolution Displays (IF 4.3) Pub Date : 2023-12-16 Qianxue Feng, Sumei Zheng, Keke Zhang, Hongan Wei
Sonar sensors are vital in the marine industry for detecting underwater targets in challenging conditions. The imaging distance and image resolution are negatively correlated due to the propagation characteristics of sound waves in water. Although Super-Resolution (SR) techniques alleviate this limitation, they introduce complex distortions that may not fit the desired utility of reconstructed sonar
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Accommodation-capable holographic waveguide head-up display with extended field of view Displays (IF 4.3) Pub Date : 2023-12-15 Woonchan Moon, Hosung Jeon, Sehwan Na, Hwi Kim, Joonku Hahn
Augmented reality (AR) displays are enhancing user experiences by offering immersive three- dimensional (3D) content, with head-up display (HUD) being a prime application for driving safety. To enable AR-HUDs to provide sufficient information to driver, it is essential to ensure a wide field of view (FOV). Traditional methods like the magnifier principle have limitations stemming from optical aberrations
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Exploiting multi-scale contextual prompt learning for zero-shot semantic segmentation Displays (IF 4.3) Pub Date : 2023-12-15 Yiqi Wang, Yingjie Tian
As traditional semantic segmentation methods evolve, they typically rely on closed-set training processes, limiting them to recognize only the classes they were trained on. To overcome this limitation, Zero-Shot Semantic Segmentation (ZSSeg) has been introduced, aiming to classify both labeled and unlabeled classes. Recently, large-scale vision-language pre-trained models, like CLIP, have gained traction
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Semantic enhancement based adaptive geometric encoding network for low overlap point cloud registration Displays (IF 4.3) Pub Date : 2023-12-13 Yuehua Zhao, Jiguang Zhang, Shibiao Xu, Jie Ma, Huishan Wang
The presence of partial or low overlaps in real point cloud pairs poses significant challenges to obtain robust registration. There is an absence of a unified framework that localizes reliable overlapping regions and correspondences. This work proposes an adaptive point cloud geometric encoding network based on semantic enhancement that generates overlap information with geometric-and-semantic consistency
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IRMultiFuseNet: Ghost hunter for infrared ship detection Displays (IF 4.3) Pub Date : 2023-12-07 Weina Zhou, Teng Ben
Infrared cameras are widely used as an supplementary sensor of visible light devices for ship detection during nocturnal journeys. However, the challenge of infrared ship detection persists due to the drawbacks of infrared images, including low resolution, contrast, and signal-to-noise ratio. In this study, we propose a unique technique that redesign existing backbone using a combined but efficient
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Smart dimming sunglasses for photophobia using spatial light modulator Displays (IF 4.3) Pub Date : 2023-12-07 Xiaodan Hu, Yan Zhang, Hideaki Uchiyama, Naoya Isoyama, Nobuchika Sakata, Kiyoshi Kiyokawa