-
MixFace: Improving face verification with a focus on fine-grained conditions ETRI J. (IF 1.4) Pub Date : 2024-03-16 Junuk Jung, Sungbin Son, Joochan Park, Yongjun Park, Seonhoon Lee, Heung-Seon Oh
The performance of face recognition (FR) has reached a plateau for public benchmark datasets, such as labeled faces in the wild (LFW), celebrities in frontal-profile in the wild (CFP-FP), and the first manually collected, in-the-wild age database (AgeDB), owing to the rapid advances in convolutional neural networks (CNNs). However, the effects of faces under various fine-grained conditions on FR models
-
Violent crowd flow detection from surveillance cameras using deep transfer learning–gated recurrent unit ETRI J. (IF 1.4) Pub Date : 2024-03-14 Elly Matul Imah, Riskyana Dewi Intan Puspitasari
Violence can be committed anywhere, even in crowded places. It is hence necessary to monitor human activities for public safety. Surveillance cameras can monitor surrounding activities but require human assistance to continuously monitor every incident. Automatic violence detection is needed for early warning and fast response. However, such automation is still challenging because of low video resolution
-
-
Special issue on speech and language AI technologies ETRI J. (IF 1.4) Pub Date : 2024-02-28 Dong-Jin Kim, Hyung-Min Park, Harksoo Kim, Seung-Hoon Na, Gerard Jounghyun Kim
Recent advancements in artificial intelligence (AI) have substantially improved applications that depend on human speech and language comprehension. Human speech, characterized by the articulation of thoughts and emotions through sounds, relies on language, a complex system that uses words and symbols for interpersonal communication. The rapid evolution of AI has amplified the demand for related solutions
-
Towards a small language model powered chain-of-reasoning for open-domain question answering ETRI J. (IF 1.4) Pub Date : 2024-02-28 Jihyeon Roh, Minho Kim, Kyoungman Bae
-
CR-M-SpanBERT: Multiple embedding-based DNN coreference resolution using self-attention SpanBERT ETRI J. (IF 1.4) Pub Date : 2024-02-28 Joon-young Jung
This study introduces CR-M-SpanBERT, a coreference resolution (CR) model that utilizes multiple embedding-based span bidirectional encoder representations from transformers, for antecedent recognition in natural language (NL) text. Information extraction studies aimed to extract knowledge from NL text autonomously and cost-effectively. However, the extracted information may not represent knowledge
-
KMSAV: Korean multi-speaker spontaneous audiovisual dataset ETRI J. (IF 1.4) Pub Date : 2024-02-28 Kiyoung Park, Changhan Oh, Sunghee Dong
Recent advances in deep learning for speech and visual recognition have accelerated the development of multimodal speech recognition, yielding many innovative results. We introduce a Korean audiovisual speech recognition corpus. This dataset comprises approximately 150 h of manually transcribed and annotated audiovisual data supplemented with additional 2000 h of untranscribed videos collected from
-
Dual-scale BERT using multi-trait representations for holistic and trait-specific essay grading ETRI J. (IF 1.4) Pub Date : 2024-02-28 Minsoo Cho, Jin-Xia Huang, Oh-Woog Kwon
As automated essay scoring (AES) has progressed from handcrafted techniques to deep learning, holistic scoring capabilities have merged. However, specific trait assessment remains a challenge because of the limited depth of earlier methods in modeling dual assessments for holistic and multi-trait tasks. To overcome this challenge, we explore providing comprehensive feedback while modeling the interconnections
-
Spoken-to-written text conversion for enhancement of Korean–English readability and machine translation ETRI J. (IF 1.4) Pub Date : 2024-02-28 HyunJung Choi, Muyeol Choi, Seonhui Kim, Yohan Lim, Minkyu Lee, Seung Yun, Donghyun Kim, Sang Hun Kim
The Korean language has written (formal) and spoken (phonetic) forms that differ in their application, which can lead to confusion, especially when dealing with numbers and embedded Western words and phrases. This fact makes it difficult to automate Korean speech recognition models due to the need for a complete transcription training dataset. Because such datasets are frequently constructed using
-
Transformer-based reranking for improving Korean morphological analysis systems ETRI J. (IF 1.4) Pub Date : 2024-02-28 Jihee Ryu, Soojong Lim, Oh-Woog Kwon, Seung-Hoon Na
This study introduces a new approach in Korean morphological analysis combining dictionary-based techniques with Transformer-based deep learning models. The key innovation is the use of a BERT-based reranking system, significantly enhancing the accuracy of traditional morphological analysis. The method generates multiple suboptimal paths, then employs BERT models for reranking, leveraging their advanced
-
2023 Reviewer List ETRI J. (IF 1.4) Pub Date : 2024-02-28
Al-Aboosi, Yasin, Univ. of Mustansiriyah A, Revathi, SASTRA Deemed Univ. A, UMAMAGESWARI, SRM Univ. - Ramapuram Campus Ab. Rahman, Azamuddin, Universiti Malaysia Pahang Al-Sultan Abdullah Abbasi, Muhammad Inam, Universiti Teknikal Malaysia Melaka Abd El-Hafeez, Tarek, Minia Univ. Abd Rahman, Mohd Amiruddin, Universiti Putra Malaysia Abdullah-Al-Shafi, Md., Univ. of Dhaka ABOLADE, Jeremiah, Pan African
-
Multistage interference cancellation for cyclic interleaved frequency division multiplexing ETRI J. (IF 1.4) Pub Date : 2024-02-26 G. Anuthirsha, S. Lenty Stuwart
Cyclic interleaved frequency division multiplexing (CIFDM), a variant of IFDM, has recently been proposed. While CIFDM employs cyclic interleaving at the transmitter to make multipath components resolvable at the receiver, the current approach of matched filtering followed by multipath combining does not fully exploit the diversity available. This is primarily because the correlation residues among
-
Suboptimal video coding for machines method based on selective activation of in-loop filter ETRI J. (IF 1.4) Pub Date : 2024-02-25 Ayoung Kim, Eun-Vin An, Soon-heung Jung, Hyon-Gon Choo, Jeongil Seo, Kwang-deok Seo
A conventional codec aims to increase the compression efficiency for transmission and storage while maintaining video quality. However, as the number of platforms using machine vision rapidly increases, a codec that increases the compression efficiency and maintains the accuracy of machine vision tasks must be devised. Hence, the Moving Picture Experts Group created a standardization process for video
-
Air quality index prediction using seasonal autoregressive integrated moving average transductive long short-term memory ETRI J. (IF 1.4) Pub Date : 2024-02-25 Subramanian Deepan, Murugan Saravanan
We obtain the air quality index (AQI) for a descriptive system aimed to communicate pollution risks to the population. The AQI is calculated based on major air pollutants including O3, CO, SO2, NO, NO2, benzene, and particulate matter PM2.5 that should be continuously balanced in clean air. Air pollution is a major limitation for urbanization and population growth in developing countries. Hence, automated
-
Finite impulse response design based on two-level transpose Vedic multiplier for medical image noise reduction ETRI J. (IF 1.4) Pub Date : 2024-02-25 Joghee Prasad, Arun Sekar Rajasekaran, J. Ajayan, Kambatty Bojan Gurumoorthy
Medical signal processing requires noise and interference-free inputs for precise segregation and classification operations. However, sensing and transmitting wireless media/devices generate noise that results in signal tampering in feature extractions. To address these issues, this article introduces a finite impulse response design based on a two-level transpose Vedic multiplier. The proposed architecture
-
Inceptionv3-LSTM-COV: A multi-label framework for identifying adverse reactions to COVID medicine from chemical conformers based on Inceptionv3 and long short-term memory ETRI J. (IF 1.4) Pub Date : 2024-02-25 Pranab Das, Dilwar Hussain Mazumder
Due to the global COVID-19 pandemic, distinct medicines have been developed for treating the coronavirus disease (COVID). However, predicting and identifying potential adverse reactions to these medicines face significant challenges in producing effective COVID medication. Accurate prediction of adverse reactions to COVID medications is crucial for ensuring patient safety and medicine success. Recent
-
Synthesis of electronically tunable multifunction biquad filter using voltage differencing differential input buffered amplifiers ETRI J. (IF 1.4) Pub Date : 2024-02-14 Sirigul Bunrueangsak, Winai Jaikla, Amornchai Chaichana, Piya Supavarasuwat, Surapong Siripongdee, Peerawut Suwanjan
Biquad filters are commonly used in analog circuits for various purposes in signal processing and communication applications. We synthesize an analog active biquad filter with five types of voltage-mode filtering functions. The filter is synthesized using a parallel passive resistor-inductor-capacitor (RLC) network and unity-gain voltage differencing amplifier. A voltage differencing differential input
-
Joint streaming model for backchannel prediction and automatic speech recognition ETRI J. (IF 1.4) Pub Date : 2024-02-14 Yong-Seok Choi, Jeong-Uk Bang, Seung Hi Kim
In human conversations, listeners often utilize brief backchannels such as “uh-huh” or “yeah.” Timely backchannels are crucial to understanding and increasing trust among conversational partners. In human–machine conversation systems, users can engage in natural conversations when a conversational agent generates backchannels like a human listener. We propose a method that simultaneously predicts backchannels
-
Named entity recognition using transfer learning and small human- and meta-pseudo-labeled datasets ETRI J. (IF 1.4) Pub Date : 2024-02-14 Kyoungman Bae, Joon-Ho Lim
We introduce a high-performance named entity recognition (NER) model for written and spoken language. To overcome challenges related to labeled data scarcity and domain shifts, we use transfer learning to leverage our previously developed KorBERT as the base model. We also adopt a meta-pseudo-label method using a teacher/student framework with labeled and unlabeled data. Our model presents two modifications
-
Multimodal audiovisual speech recognition architecture using a three-feature multi-fusion method for noise-robust systems ETRI J. (IF 1.4) Pub Date : 2024-02-14 Sanghun Jeon, Jieun Lee, Dohyeon Yeo, Yong-Ju Lee, SeungJun Kim
Exposure to varied noisy environments impairs the recognition performance of artificial intelligence-based speech recognition technologies. Degraded-performance services can be utilized as limited systems that assure good performance in certain environments, but impair the general quality of speech recognition services. This study introduces an audiovisual speech recognition (AVSR) model robust to
-
Framework for evaluating code generation ability of large language models ETRI J. (IF 1.4) Pub Date : 2024-02-14 Sangyeop Yeo, Yu-Seung Ma, Sang Cheol Kim, Hyungkook Jun, Taeho Kim
Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and introduce a new metric, pass-ratio@n, which captures the granularity of accuracy according to the pass rate of test cases. The framework is intended to be fully
-
Performance analysis of multiview video compression based on MIV and VVC multilayer ETRI J. (IF 1.4) Pub Date : 2024-02-01 Jinho Lee, Gun Bang, Jungwon Kang, Mehrdad Teratani, Gauthier Lafruit, Haechul Choi
To represent immersive media providing six degree-of-freedom experience, moving picture experts group (MPEG) immersive video (MIV) was developed to compress multiview videos. Meanwhile, the state-of-the-art versatile video coding (VVC) also supports multilayer (ML) functionality, enabling the coding of multiview videos. In this study, we designed experimental conditions to assess the performance of
-
AI-based language tutoring systems with end-to-end automatic speech recognition and proficiency evaluation ETRI J. (IF 1.4) Pub Date : 2024-01-31 Byung Ok Kang, Hyung-Bae Jeon, Yun Kyung Lee
This paper presents the development of language tutoring systems for non-native speakers by leveraging advanced end-to-end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non-native speech, high-performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying
-
Alzheimer's disease recognition from spontaneous speech using large language models ETRI J. (IF 1.4) Pub Date : 2024-01-29 Jeong-Uk Bang, Seung-Hoon Han, Byung-Ok Kang
We propose a method to automatically predict Alzheimer's disease from speech data using the ChatGPT large language model. Alzheimer's disease patients often exhibit distinctive characteristics when describing images, such as difficulties in recalling words, grammar errors, repetitive language, and incoherent narratives. For prediction, we initially employ a speech recognition system to transcribe participants'
-
Single-shot phase-shifting on Michelson interferometry for incoherent digital holography ETRI J. (IF 1.4) Pub Date : 2024-01-26 Keehoon Hong, Kihong Choi
A single-shot phase-shifting method in incoherent digital holography (IDH) based on Michelson interferometry is proposed herein. The proposed method uses polarization-modulating optical elements and a polarization sensor in the Michelson interferometer optics to induce a geometric phase shift. It acquires four holograms with different geometric phase retardations in a single exposure to eliminate the
-
Design and simulation of a rectangular planar printed circuit board coil for nuclear magnetic resonance, radio frequency energy harvesting, and wireless power transfer devices ETRI J. (IF 1.4) Pub Date : 2024-01-17 Mostafa Noohi, Adel Pourmand, Habib Badri Ghavifekr, Ali Mirvakili
In this study, a planar printed circuit board (PCB) coil with FR4 substrate was designed and simulated using the finite element method, and the results were analyzed in the frequency domain. This coil can be used in wireless power transfer (WPT) as a transmitter or receiver, eliminating wires. It can also be used as the receiver in radio frequency energy-harvesting (RF-EH) systems by optimizing the
-
Providing scalable single-operating-system NUMA abstraction of physically discrete resources ETRI J. (IF 1.4) Pub Date : 2024-01-16 Baik Song An, Myung Hoon Cha, Sang-Min Lee, Won Hyuk Yang, Hong Yeon Kim
With an explosive increase of data produced annually, researchers have been attempting to develop solutions for systems that can effectively handle large amounts of data. Single-operating-system (OS) non-uniform memory access (NUMA) abstraction technology is an important technology that ensures the compatibility of single-node programming interfaces across multiple nodes owing to its higher cost efficiency
-
Polar coded cooperative with Plotkin construction and quasi-uniform puncturing based on MIMO antennas in half duplex wireless relay network ETRI J. (IF 1.4) Pub Date : 2024-01-16 Jiangli Zeng, Sanya Liu
Recently, polar code has attracted the attention of many scholars and has been developed as a code technology in coded-cooperative communication. We propose a polar code scheme based on Plotkin structure and quasi-uniform punching (PC-QUP). Then we apply the PC-QUP to coded-cooperative scenario and built to a new coded-cooperative scheme, which is called PCC-QUP scheme. The coded-cooperative scheme
-
Deep reinforcement learning for base station switching scheme with federated LSTM-based traffic predictions ETRI J. (IF 1.4) Pub Date : 2024-01-12 Hyebin Park, Seung Hyun Yoon
To meet increasing traffic requirements in mobile networks, small base stations (SBSs) are densely deployed, overlapping existing network architecture and increasing system capacity. However, densely deployed SBSs increase energy consumption and interference. Although these problems already exist because of densely deployed SBSs, even more SBSs are needed to meet increasing traffic demands. Hence,
-
Joint user plane function instance and base station scheduling in mobile networks ETRI J. (IF 1.4) Pub Date : 2023-12-16 Seokwon Jang, Namseok Ko, Jaewook Lee, Yeunwoong Kyung, Haneul Ko
To guarantee a high data transmission rate in heterogeneous mobile networks, sufficient small base stations (SBSs) and user plane function (UPF) instances should be active. However, the excessive operation of SBSs and UPF instances can increase the operating expenditure (OPEX) for the network operator. To balance the data rate and OPEX, we propose a joint UPF instance–SBS scheduling algorithm (J-UBSA)
-
Dialog-based multi-item recommendation using automatic evaluation ETRI J. (IF 1.4) Pub Date : 2023-12-14 Euisok Chung, Hyun Woo Kim, Byunghyun Yoo, Ran Han, Jeongmin Yang, Hwa Jeon Song
In this paper, we describe a neural network-based application that recommends multiple items using dialog context input and simultaneously outputs a response sentence. Further, we describe a multi-item recommendation by specifying it as a set of clothing recommendations. For this, a multimodal fusion approach that can process both cloth-related text and images is required. We also examine achieving
-
-
Symbol interferometry and companding transform for PAPR reduction of OTFS signal ETRI J. (IF 1.4) Pub Date : 2023-12-06 Aare Gopal, Desireddy Krishna Reddy, Srinivasarao Chintagunta
This paper presents methods for reducing the peak-to-average power ratio (PAPR) of the orthogonal time frequency space (OTFS) signal. These methods mainly consist of two operations: symbol interferometry (SI) and either μ $$ \mu $$ -law or A $$ A $$ -law companding. SI spreads the data of one OTFS symbol onto all symbols and is implemented using a simple inverse fast Fourier transform operation on
-
On the block error rate performance of cooperative non-orthogonal multiple access short-packet communications with full-duplex relay and partial relay selection ETRI J. (IF 1.4) Pub Date : 2023-12-06 Ha Duy Hung, Hoang Van Toan, Tran Trung Duy, Le The Dung, Quang Sy Vu
In this paper, we mathematically investigate a downlink non-orthogonal multiple access (NOMA) system for short-packet communications (SPC) in which the near users are used as full-duplex (FD) relays to forward intended signals from the source to a far user. In addition, partial relay selection is employed to enhance the performance of the FD relays under the impact of imperfect interference cancellation
-
Relay-assisted multiuser MIMO-DQSM system for correlated fading channels ETRI J. (IF 1.4) Pub Date : 2023-11-29 Francisco R. Castillo-Soria, Carlos Gutierrez, Fermin M. Maciel-Barboza, Viktor I. Rodriguez Abdala, Jayanta Datta
This paper presents the performance evaluation of an amplify-and-forward (AF) relay-assisted multiuser multiple input–multiple output (MU–MIMO) downlink transmission system for correlated fading channels. The overall system performance was improved by incorporating a double-quadrature spatial modulation (DQSM) scheme. The bit error rate (BER) performance and detection complexity of the AF–MU–MIMO–DQSM
-
Direct position tracking method for non-circular signals with distributed passive arrays via first-order approximation ETRI J. (IF 1.4) Pub Date : 2023-11-23 Jinke Cao, Xiaofei Zhang, Honghao Hao
In this study, a direct position tracking method for non-circular (NC) signals using distributed passive arrays is proposed. First, we calculate the initial positions of sources using a direct position determination (DPD) approach; next, we transform the tracking into a compensation problem. The offsets of the adjacent time positions are calculated using a first-order Taylor expansion. The fusion calculation
-
Oriented object detection in satellite images using convolutional neural network based on ResNeXt ETRI J. (IF 1.4) Pub Date : 2023-11-22 Asep Haryono, Grafika Jati, Wisnu Jatmiko
Most object detection methods use a horizontal bounding box that causes problems between adjacent objects with arbitrary directions, resulting in misaligned detection. Hence, the horizontal anchor should be replaced by a rotating anchor to determine oriented bounding boxes. A two-stage process of delineating a horizontal bounding box and then converting it into an oriented bounding box is inefficient
-
Substrate-integrated-waveguide cavity-backed circularly polarized antenna with enhanced bandwidth and gain ETRI J. (IF 1.4) Pub Date : 2023-11-22 Shankaragouda M. Patil, Rajeshkumar Venkatesan
We propose a method for increasing the bandwidth of a substrate-integrated-waveguide (SIW) cavity-backed antenna with taper-based microstrip SIW transition feeding. For radio transmission, a circular slot is etched on top of the SIW cavity. For optimal antenna design, the slot is etched slightly away from the cavity center to generate circularly polarized waves. Simulations show a wide axial ratio
-
Numerical analysis of quantization-based optimization ETRI J. (IF 1.4) Pub Date : 2023-11-22 Jinwuk Seok, Chang Sik Cho
We propose a number-theory-based quantized mathematical optimization scheme for various NP-hard and similar problems. Conventional global optimization schemes, such as simulated and quantum annealing, assume stochastic properties that require multiple attempts. Although our quantization-based optimization proposal also depends on stochastic features (i.e., the white-noise hypothesis), it provides a
-
10-GHz band 2 × 2 phased-array radio frequency receiver with 8-bit linear phase control and 15-dB gain control range using 65-nm complementary metal–oxide–semiconductor technology ETRI J. (IF 1.4) Pub Date : 2023-11-07 Seon-Ho Han, Bon-Tae Koo
We propose a 10-GHz 2 × 2 phased-array radio frequency (RF) receiver with an 8-bit linear phase and 15-dB gain control range using 65-nm complementary metal–oxide–semiconductor technology. An 8 × 8 phased-array receiver module is implemented using 16 2 × 2 RF phased-array integrated circuits. The receiver chip has four single-to-differential low-noise amplifier and gain-controlled phase-shifter (GCPS)
-
Compact near-eye display for firefighter's self-contained breathing apparatus ETRI J. (IF 1.4) Pub Date : 2023-11-07 Ungyeon Yang
We introduce a display for virtual-reality (VR) fire training. Firefighters prefer to wear and operate a real breathing apparatus while experiencing full visual immersion in a VR fire space. Thus, we used a thin head-mounted display (HMD) with a light field and folded optical system, aiming to both minimize the volume for integration in front of the face into a breathing apparatus and maintain adequate
-
Transfer-learning-based classification of pathological brain magnetic resonance images ETRI J. (IF 1.4) Pub Date : 2023-10-29 Serkan Savaş, Çağrı Damar
Different diseases occur in the brain. For instance, hereditary and progressive diseases affect and degenerate the white matter. Although addressing, diagnosing, and treating complex abnormalities in the brain is challenging, different strategies have been presented with significant advances in medical research. With state-of-art developments in artificial intelligence, new techniques are being applied
-
Design and analysis of highly selective ultrawide stopband lowpass filter using lumped and distributed equivalent circuit models ETRI J. (IF 1.4) Pub Date : 2023-10-25 Pankaj Singh Tomar, Manoj Singh Parihar
An ultrawide stopband lowpass filter is reported using three stepped impedance resonators with high selectivity. The filter extends the stopband frequency range and attenuation, and two quarter-wave open stubs and three circular ground slots are introduced. The lumped and distributed equivalent models are derived and analyzed. The corresponding results are validated experimentally in a fabricated prototype
-
-
Special issue on autonomous unmanned aerial/ground vehicles and their applications ETRI J. (IF 1.4) Pub Date : 2023-10-29 Joongheon Kim, Yu-Cheol Lee, Jun Hwan Lee, Jin Seek Choi
Recently, research on autonomous mobility control has been actively and widely conducted for various applications. In particular, autonomous mobility control for unmanned aerial and ground vehicles has been our research interest because it has considerable challenges, such as time-consuming and high-delay computations, complicated functionalities, and dangerous tasks that were previously performed
-
Real-time collision-free landing path planning for drone deliveries in urban environments ETRI J. (IF 1.4) Pub Date : 2023-10-29 Hanseob Lee, Sungwook Cho, Hoon Jung
This study presents a novel safe landing algorithm for urban drone deliveries. The rapid advancement of drone technology has given rise to various delivery services for everyday necessities and emergency relief efforts. However, the reliability of drone delivery technology is still insufficient for application in urban environments. The proposed approach uses the “landing angle control” method to allow
-
Ultrawideband coupled relative positioning algorithm applicable to flight controller for multidrone collaboration ETRI J. (IF 1.4) Pub Date : 2023-10-29 Jeonggi Yang, Soojeon Lee
In this study, we introduce a loosely coupled relative position estimation method that utilizes a decentralized ultrawideband (UWB), Global Navigation Support System and inertial navigation system for flight controllers (FCs). Key obstacles to multidrone collaboration include relative position errors and the absence of communication devices. To address this, we provide an extended Kalman filter-based
-
Implementation of mmWave long-range backhaul for UAV-BS ETRI J. (IF 1.4) Pub Date : 2023-10-29 Jangwon Moon, Junwoo Kim, Hoon Lee, Youngjin Moon, Yongsu Lee, Youngjo Bang, Kyungyeol Sohn, Jungsook Bae, Kwangseon Kim, Seungjae Bahng, Heesoo Lee
Uncrewed aerial vehicles (UAVs) have become a vital element in nonterrestrial networks, especially with respect to 5G communication systems and beyond. The use of UAVs in support of 4G/5G base station (uncrewed aerial vehicle base station [UAV-BS]) has proven to be a practical solution for extending cellular network services to areas where conventional infrastructures are unavailable. In this study
-
Joint frame rate adaptation and object recognition model selection for stabilized unmanned aerial vehicle surveillance ETRI J. (IF 1.4) Pub Date : 2023-10-28 Gyu Seon Kim, Haemin Lee, Soohyun Park, Joongheon Kim
We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore
-
Assembling three one-camera images for three-camera intersection classification ETRI J. (IF 1.4) Pub Date : 2023-10-29 Marcella Astrid, Seung-Ik Lee
Determining whether an autonomous self-driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training
-
Artificial neural network for safety information dissemination in vehicle-to-internet networks ETRI J. (IF 1.4) Pub Date : 2023-10-18 Ramesh B. Koti, Mahabaleshwar S. Kakkasageri, Rajani S. Pujar
In vehicular networks, diverse safety information can be shared among vehicles through internet connections. In vehicle-to-internet communications, vehicles on the road are wirelessly connected to different cloud networks, thereby accelerating safety information exchange. Onboard sensors acquire traffic-related information, and reliable intermediate nodes and network services, such as navigational
-
A conditionally applied neural network algorithm for PAPR reduction without the use of a recovery process ETRI J. (IF 1.4) Pub Date : 2023-10-16 Eldaw E. Eldukhri, Mohammed I. Al-Rayif
This study proposes a novel, conditionally applied neural network technique to reduce the overall peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) system while maintaining an acceptable bit error rate (BER) level. The main purpose of the proposed scheme is to adjust only those subcarriers whose peaks exceed a given threshold. In this respect, the developed
-
Performance analysis of atomic magnetometer and bandwidth-extended loop antenna in resonant phase-modulated magnetic field communication system ETRI J. (IF 1.4) Pub Date : 2023-10-10 Hyun Joon Lee, Jung Hoon Oh, Jang-Yeol Kim, In-Kui Cho
Telecommunications through an electrically conductive medium require the use of carrier bands with very-low and ultralow frequencies to establish radiofrequency links in harsh environments. Recent advances in atomic magnetometers operating at very-low frequencies have facilitated the reception of digitally modulated signals. We demonstrate the transmission and reception of quadrature phase-shift keying
-
Two tales of platoon intelligence for autonomous mobility control: Enabling deep learning recipes ETRI J. (IF 1.4) Pub Date : 2023-10-09 Soohyun Park, Haemin Lee, Chanyoung Park, Soyi Jung, Minseok Choi, Joongheon Kim
This paper surveys recent multiagent reinforcement learning and neural Myerson auction deep learning efforts to improve mobility control and resource management in autonomous ground and aerial vehicles. The multiagent reinforcement learning communication network (CommNet) was introduced to enable multiple agents to perform actions in a distributed manner to achieve shared goals by training all agents'
-
Time-reversal microwave focusing using multistatic data ETRI J. (IF 1.4) Pub Date : 2023-09-29 Won-Young Song, Soon-Ik Jeon, Seong-Ho Son, Kwang-Jae Lee
Various techniques for noninvasively focus microwave energy on lesions have been proposed for thermotherapy. To focus the microwave energy on the lesion, a focusing parameter, which is referred to as the magnitude and phase of microwaves radiated from an external array antenna, is very important. Although the finite-difference time-domain (FDTD)-based time-reversal (TR) focusing algorithm is widely
-
CRFNet: Context ReFinement Network used for semantic segmentation ETRI J. (IF 1.4) Pub Date : 2023-10-04 Taeghyun An, Jungyu Kang, Dooseop Choi, Kyoung-Wook Min
Recent semantic segmentation frameworks usually combine low-level and high-level context information to achieve improved performance. In addition, postlevel context information is also considered. In this study, we present a Context ReFinement Network (CRFNet) and its training method to improve the semantic predictions of segmentation models of the encoder–decoder structure. Our study is based on postprocessing
-
EMOS: Enhanced moving object detection and classification via sensor fusion and noise filtering ETRI J. (IF 1.4) Pub Date : 2023-09-25 Dongjin Lee, Seung-Jun Han, Kyoung-Wook Min, Jungdan Choi, Cheong Hee Park
Dynamic object detection is essential for ensuring safe and reliable autonomous driving. Recently, light detection and ranging (LiDAR)-based object detection has been introduced and shown excellent performance on various benchmarks. Although LiDAR sensors have excellent accuracy in estimating distance, they lack texture or color information and have a lower resolution than conventional cameras. In
-
A three-dimensional two-hemisphere model for unmanned aerial vehicle multiple-input multiple-output channels ETRI J. (IF 1.4) Pub Date : 2023-09-20 Zixu Su, Wei Chen, Changzhen Li, Junyi Yu, Guojiao Gong, Zixin Wang
The application of unmanned aerial vehicles (UAVs) has recently attracted considerable interest in various areas. A three-dimensional multiple-input multiple-output concentric two-hemisphere model is proposed to characterize the scattering environment around a vehicle in an urban UAV-to-vehicle communication scenario. Multipath components of the model consisted of line-of-sight and single-bounced components
-
Background memory-assisted zero-shot video object segmentation for unmanned aerial and ground vehicles ETRI J. (IF 1.4) Pub Date : 2023-09-20 Kimin Yun, Hyung-Il Kim, Kangmin Bae, Jinyoung Moon
Unmanned aerial vehicles (UAV) and ground vehicles (UGV) require advanced video analytics for various tasks, such as moving object detection and segmentation; this has led to increasing demands for these methods. We propose a zero-shot video object segmentation method specifically designed for UAV and UGV applications that focuses on the discovery of moving objects in challenging scenarios. This method
-
Real-time 3D multi-pedestrian detection and tracking using 3D LiDAR point cloud for mobile robot ETRI J. (IF 1.4) Pub Date : 2023-09-16 Ki-In Na, Byungjae Park
Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light