当前期刊: "应用"类期刊
显示样式:        排序: 导出
我的关注
我的收藏
您暂时未登录!
登录
  • A dual scaled boundary finite element formulation over arbitrary faceted star convex polyhedra
    Comput. Mech. (IF 3.159) Pub Date : 2020-03-27
    E. T. Ooi, A. Saputra, S. Natarajan, E. H. Ooi, C. Song

    Abstract A novel technique to formulate arbritrary faceted polyhedral elements in three-dimensions is presented. The formulation is applicable for arbitrary faceted polyhedra, provided that a scaling requirement is satisfied and the polyhedron facets are planar. A triangulation process can be applied to non-planar facets to generate an admissible geometry. The formulation adopts two separate scaled

    更新日期:2020-03-28
  • Numerical modeling of the fractured zones around a blasthole
    Comput. Geotech. (IF 3.345) Pub Date : 2020-03-27
    A.R. Hajibagherpour; H. Mansouri; M. Bahaaddini

    The high-energy rate of shock waves, as an important part of explosion energy, plays a significant role in the mechanism of rock fragmentation. This energy rate and the mechanism of rock fracturing are controlled by several parameters related to both the explosive charge and rock mechanical properties. In this study, the mechanism of rock fragmentation due to blast-induced shock waves in a single blasthole

    更新日期:2020-03-28
  • Non-parallel Voice Conversion System with WaveNet Vocoder and Collapsed Speech Suppression
    arXiv.cs.SD Pub Date : 2020-03-26
    Yi-Chiao Wu; Patrick Lumban Tobing; Kazuhiro Kobayashi; Tomoki Hayashi; Tomoki Toda

    In this paper, we integrate a simple non-parallel voice conversion (VC) system with a WaveNet (WN) vocoder and a proposed collapsed speech suppression technique. The effectiveness of WN as a vocoder for generating high-fidelity speech waveforms on the basis of acoustic features has been confirmed in recent works. However, when combining the WN vocoder with a VC system, the distorted acoustic features

    更新日期:2020-03-28
  • Finnish Language Modeling with Deep Transformer Models
    arXiv.cs.SD Pub Date : 2020-03-14
    Abhilash Jain

    Transformers have recently taken the center stage in language modeling after LSTM's were considered the dominant model architecture for a long time. In this project, we investigate the performance of the Transformer architectures-BERT and Transformer-XL for the language modeling task. We use a sub-word model setting with the Finnish language and compare it to the previous State of the art (SOTA) LSTM

    更新日期:2020-03-28
  • Speech Quality Factors for Traditional and Neural-Based Low Bit Rate Vocoders
    arXiv.cs.SD Pub Date : 2020-03-26
    Wissam A. Jassim; Jan Skoglund; Michael Chinen; Andrew Hines

    This study compares the performances of different algorithms for coding speech at low bit rates. In addition to widely deployed traditional vocoders, a selection of recently developed generative-model-based coders at different bit rates are contrasted. Performance analysis of the coded speech is evaluated for different quality aspects: accuracy of pitch periods estimation, the word error rates for

    更新日期:2020-03-28
  • In defence of metric learning for speaker recognition
    arXiv.cs.SD Pub Date : 2020-03-26
    Joon Son Chung; Jaesung Huh; Seongkyu Mun; Minjae Lee; Hee Soo Heo; Soyeon Choe; Chiheon Ham; Sunghwan Jung; Bong-Jin Lee; Icksang Han

    The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level representation that has small intra-class (same speaker) and large inter-class (different speakers) distance. A popular belief in speaker recognition is that networks trained with classification objectives outperform metric learning

    更新日期:2020-03-28
  • Unfair Exposure of Artists in Music Recommendation
    arXiv.cs.IR Pub Date : 2020-03-25
    Himan Abdollahpouri; Robin Burke; Masoud Mansoury

    Fairness in machine learning has been studied by many researchers. In particular, fairness in recommender systems has been investigated to ensure the recommendations meet certain criteria with respect to certain sensitive features such as race, gender etc. However, often recommender systems are multi-stakeholder environments in which the fairness towards all stakeholders should be taken care of. It

    更新日期:2020-03-28
  • Overview of the TREC 2019 Fair Ranking Track
    arXiv.cs.IR Pub Date : 2020-03-25
    Asia J. Biega; Fernando Diaz; Michael D. Ekstrand; Sebastian Kohlmeier

    The goal of the TREC Fair Ranking track was to develop a benchmark for evaluating retrieval systems in terms of fairness to different content providers in addition to classic notions of relevance. As part of the benchmark, we defined standardized fairness metrics with evaluation protocols and released a dataset for the fair ranking problem. The 2019 task focused on reranking academic paper abstracts

    更新日期:2020-03-28
  • Top Comment or Flop Comment? Predicting and Explaining User Engagement in Online News Discussions
    arXiv.cs.IR Pub Date : 2020-03-26
    Julian Risch; Ralf Krestel

    Comment sections below online news articles enjoy growing popularity among readers. However, the overwhelming number of comments makes it infeasible for the average news consumer to read all of them and hinders engaging discussions. Most platforms display comments in chronological order, which neglects that some of them are more relevant to users and are better conversation starters. In this paper

    更新日期:2020-03-28
  • Creating Personas with Disabilities
    arXiv.cs.HC Pub Date : 2020-03-26
    Trenton Schulz; Kristin Skeide Fuglerud

    Personas can help raise awareness among stakeholders about users' needs. While personas are made-up people, they are based on facts gathered from user research. Personas can also be used to raise awareness of universal design and accessibility needs of people with disabilities. We review the current state of the art of the personas and review some research and industry projects that use them. We outline

    更新日期:2020-03-28
  • Pedestrian Models for Autonomous Driving Part II: high level models of human behaviour
    arXiv.cs.HC Pub Date : 2020-03-26
    Fanta Camara; Nicola Bellotto; Serhan Cosar; Florian Weber; Dimitris Nathanael; Matthias Althoff; Jingyuan Wu; Johannes Ruenz; André Dietrich; Gustav Markkula; Anna Schieben; Fabio Tango; Natasha Merat; Charles W. Fox

    Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on high-streets. Unlike static and kinematic obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their

    更新日期:2020-03-28
  • On-Line Permissive Supervisory Control of Discrete Event Systems for scLTL Specifications
    arXiv.cs.FL Pub Date : 2020-03-26
    Ami Sakakibara; Toshimitsu Ushio

    We propose an on-line supervisory control scheme for discrete event systems (DESs), where a control specification is described by a fragment of linear temporal logic. On the product automaton of the DES and an acceptor for the specification, we define a ranking function that returns the minimum number of steps required to reach an accepting state from each state. In addition, we introduce a permissiveness

    更新日期:2020-03-28
  • Minimising Good-for-Games automata is NP complete
    arXiv.cs.FL Pub Date : 2020-03-26
    Sven Schewe

    This paper discusses the hardness of finding minimal good-for-games (GFG) Buchi, Co-Buchi, and parity automata with state based acceptance. The problem appears to sit between finding small deterministic and finding small nondeterministic automata, where minimality is NP-complete and PSPACE-complete, respectively. However, recent work of Radi and Kupferman has shown that minimising Co-Buchi automata

    更新日期:2020-03-28
  • Equivalence checking for weak bi-Kleene algebra
    arXiv.cs.FL Pub Date : 2018-07-05
    Tobias Kappé; Paul Brunet; Bas Luttik; Alexandra Silva; Fabio Zanasi

    Pomset automata are an operational model of weak bi-Kleene algebra, which describes programs that can fork an execution into parallel threads, upon completion of which execution can join to resume as a single thread. We characterize a fragment of pomset automata that admits a decision procedure for language equivalence. Furthermore, we prove that this fragment corresponds precisely to series-rational

    更新日期:2020-03-28
  • Deep Multicameral Decoding for Localizing Unoccluded Object Instances from a Single RGB Image
    Int. J. Comput. Vis. (IF 6.071) Pub Date : 2020-03-27
    Matthieu Grard, Emmanuel Dellandréa, Liming Chen

    Abstract Occlusion-aware instance-sensitive segmentation is a complex task generally split into region-based segmentations, by approximating instances as their bounding box. We address the showcase scenario of dense homogeneous layouts in which this approximation does not hold. In this scenario, outlining unoccluded instances by decoding a deep encoder becomes difficult, due to the translation invariance

    更新日期:2020-03-27
  • Convolutional neural networks for pavement roughness assessment using calibration‐free vehicle dynamics
    Comput. Aided Civ. Infrastruct. Eng. (IF 6.208) Pub Date : 2020-03-27
    Jong‐Hyun Jeong; Hongki Jo; Gregory Ditzler

    Road roughness is a measure of how uncomfortable a ride is, and provides an important indicator for the needs of roadway maintenance or repavement, which is closely tied to the state and federal budget prioritization. As such, accurate and timely monitoring of deteriorating road conditions and following maintenance are essential to improve the overall ride quality on the road. Various technologies

    更新日期:2020-03-27
  • A Kane’s based algorithm for closed-form dynamic analysis of a new design of a 3RSS-S spherical parallel manipulator
    Multibody Syst. Dyn. (IF 2.364) Pub Date : 2020-03-27
    Javad Enferadi, Keyvan Jafari

    Abstract This paper proposes a systematic methodology to obtain a closed-form formulation for dynamics analysis of a new design of a fully spherical robot that is called a 3(RSS)-S parallel manipulator with real co-axial actuated shafts. The proposed robot can completely rotate about a vertical axis and can be used in celestial orientation and rehabilitation applications. After describing the robot

    更新日期:2020-03-27
  • Multimedia content recommendation in social networks using mood tags and synonyms
    Multimedia Syst. (IF 1.956) Pub Date : 2019-08-14
    Chang Bae Moon, Jong Yeol Lee, Dong-Seong Kim, Byeong Man Kim

    Abstract The preferences of Web information purchasers are changing. Cost-effectiveness (i.e., an emphasis on performance with respect to price) is becoming less regarded than cost-satisfaction, which emphasizes the purchaser’s psychological satisfaction. A method to improve a user’s cost-satisfaction in recommending multimedia content is to use the mood-inherent in multimedia items. An example of

    更新日期:2020-03-27
  • On improving the engagement between viewers and TV commercials through gamification
    Multimedia Syst. (IF 1.956) Pub Date : 2019-06-25
    Marco Furini, Roberta De Michele

    Abstract TV advertisements are less and less watched as most viewers turn their attention to the smartphone during commercial breaks. Therefore, broadcasters are facing a novel challenge: how to improve the engagement between viewers and TV commercials. In this paper, we investigate whether gamification can be a winning strategy. Indeed, despite some strategies that have recently been proposed (e.g

    更新日期:2020-03-27
  • RMoCap: an R language package for processing and kinematic analyzing motion capture data
    Multimedia Syst. (IF 1.956) Pub Date : 2019-08-31
    Tomasz Hachaj, Marek R. Ogiela

    Abstract Package RMoCap is an advanced open-source tool for scientists, engineers and computer graphics familiar with R language who work with motion capture (MoCap) technology. Package provides them with MoCap data handling, statistical processing, visualizing and analysis. Package uses well-established MoCap file exchange format and can be easily integrated with most of the motion analysis workflows

    更新日期:2020-03-27
  • A steganographic method based on gain quantization for iLBC speech streams
    Multimedia Syst. (IF 1.956) Pub Date : 2019-06-25
    Zhaopin Su, Wangwang Li, Guofu Zhang, Donghui Hu, Xianxian Zhou

    Abstract Under the premise of ensuring good speech quality and resistance to steganalysis, how to embed as much information as possible into low-bit-rate speech is a challenge. The existing research mainly focuses on least significant bits in the compressed speech streams or line spectral frequencies in the encoding processes of the G.723.1 and G.729a codecs. In this paper, we are concentrating on

    更新日期:2020-03-27
  • A real-time 3D video analyzer for enhanced 3D audio–visual systems
    Multimedia Syst. (IF 1.956) Pub Date : 2019-08-07
    Sangoh Jeong, Hyun-Soo Kim, KyuWoon Kim, Byeong-Moon Jeon, Joong-Ho Won

    Abstract With the recent advent of three-dimensional (3D) sound home theater systems (HTS), more and more TV viewers are experiencing rich, immersive auditory presence at home. In this paper, visual processing approaches are provided to make 3D audio–visual (AV) systems more realistic to the viewers. In the proposed system, a visual engine processes stereo video streams to extract a disparity map for

    更新日期:2020-03-27
  • Learning One-Clock Timed Automata
    arXiv.cs.FL Pub Date : 2019-10-23
    Jie An; Mingshuai Chen; Bohua Zhan; Naijun Zhan; Miaomiao Zhang

    We present an algorithm for active learning of deterministic timed automata with a single clock. The algorithm is within the framework of Angluin's $L^*$ algorithm and inspired by existing work on the active learning of symbolic automata. Due to the need of guessing for each transition whether it resets the clock, the algorithm is of exponential complexity in the size of the learned automata. Before

    更新日期:2020-03-27
  • Forensic Authorship Analysis of Microblogging Texts Using N-Grams and Stylometric Features
    arXiv.cs.CL Pub Date : 2020-03-24
    Nicole Mariah Sharon Belvisi; Naveed Muhammad; Fernando Alonso-Fernandez

    In recent years, messages and text posted on the Internet are used in criminal investigations. Unfortunately, the authorship of many of them remains unknown. In some channels, the problem of establishing authorship may be even harder, since the length of digital texts is limited to a certain number of characters. In this work, we aim at identifying authors of tweet messages, which are limited to 280

    更新日期:2020-03-27
  • Predicting Legal Proceedings Status: an Approach Based on Sequential Text Data
    arXiv.cs.CL Pub Date : 2020-03-13
    Felipe Maia Polo; Itamar Ciochetti; Emerson Bertolo

    Machine learning applications in the legal field are numerous and diverse. In order to make contribution to both the machine learning community and the legal community, we have made efforts to create a model compatible with the classification of text sequences, valuing the interpretability of the results. The purpose of this paper is to classify legal proceedings in three possible status classes, which

    更新日期:2020-03-27
  • Finnish Language Modeling with Deep Transformer Models
    arXiv.cs.CL Pub Date : 2020-03-14
    Abhilash Jain

    Transformers have recently taken the center stage in language modeling after LSTM's were considered the dominant model architecture for a long time. In this project, we investigate the performance of the Transformer architectures-BERT and Transformer-XL for the language modeling task. We use a sub-word model setting with the Finnish language and compare it to the previous State of the art (SOTA) LSTM

    更新日期:2020-03-27
  • Cost-Sensitive BERT for Generalisable Sentence Classification with Imbalanced Data
    arXiv.cs.CL Pub Date : 2020-03-16
    Harish Tayyar Madabushi; Elena Kochkina; Michael Castelle

    The automatic identification of propaganda has gained significance in recent years due to technological and social changes in the way news is generated and consumed. That this task can be addressed effectively using BERT, a powerful new architecture which can be fine-tuned for text classification tasks, is not surprising. However, propaganda detection, like other tasks that deal with news documents

    更新日期:2020-03-27
  • Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
    arXiv.cs.CL Pub Date : 2020-03-25
    Hamid Jalalzai; Pierre Colombo; Chloé Clavel; Eric Gaussier; Giovanna Varni; Emmanuel Vignon; Anne Sabourin

    The dominant approaches to text representation in natural language rely on learning embeddings on massive corpora which have convenient properties such as compositionality and distance preservation. In this paper, we develop a novel method to learn a heavy-tailed embedding with desirable regularity properties regarding the distributional tails, which allows to analyze the points far away from the distribution

    更新日期:2020-03-27
  • VIOLIN: A Large-Scale Dataset for Video-and-Language Inference
    arXiv.cs.CL Pub Date : 2020-03-25
    Jingzhou Liu; Wenhu Chen; Yu Cheng; Zhe Gan; Licheng Yu; Yiming Yang; Jingjing Liu

    We introduce a new task, Video-and-Language Inference, for joint multimodal understanding of video and text. Given a video clip with aligned subtitles as premise, paired with a natural language hypothesis based on the video content, a model needs to infer whether the hypothesis is entailed or contradicted by the given video clip. A new large-scale dataset, named Violin (VIdeO-and-Language INference)

    更新日期:2020-03-27
  • Predicting Unplanned Readmissions with Highly Unstructured Data
    arXiv.cs.CL Pub Date : 2020-03-19
    Constanza Fierro; Jorge Pérez; Javier Mora

    Deep learning techniques have been successfully applied to predict unplanned readmissions of patients in medical centers. The training data for these models is usually based on historical medical records that contain a significant amount of free-text from admission reports, referrals, exam notes, etc. Most of the models proposed so far are tailored to English text data and assume that electronic medical

    更新日期:2020-03-27
  • Author2Vec: A Framework for Generating User Embedding
    arXiv.cs.CL Pub Date : 2020-03-17
    Xiaodong Wu; Weizhe Lin; Zhilin Wang; Elena Rastorgueva

    Online forums and social media platforms provide noisy but valuable data every day. In this paper, we propose a novel end-to-end neural network-based user embedding system, Author2Vec. The model incorporates sentence representations generated by BERT (Bidirectional Encoder Representations from Transformers) with a novel unsupervised pre-training objective, authorship classification, to produce better

    更新日期:2020-03-27
  • Sentiment Analysis in Drug Reviews using Supervised Machine Learning Algorithms
    arXiv.cs.CL Pub Date : 2020-03-21
    Sairamvinay Vijayaraghavan; Debraj Basu

    Sentiment Analysis is an important algorithm in Natural Language Processing which is used to detect sentiment within some text. In our project, we had chosen to work on analyzing reviews of various drugs which have been reviewed in form of texts and have also been given a rating on a scale from 1-10. We had obtained this data set from the UCI machine learning repository which had 2 data sets: train

    更新日期:2020-03-27
  • Multi-Label Text Classification using Attention-based Graph Neural Network
    arXiv.cs.CL Pub Date : 2020-03-22
    Ankit Pal; Muru Selvakumar; Malaikannan Sankarasubbu

    In Multi-Label Text Classification (MLTC), one sample can belong to more than one class. It is observed that most MLTC tasks, there are dependencies or correlations among labels. Existing methods tend to ignore the relationship among labels. In this paper, a graph attention network-based model is proposed to capture the attentive dependency structure among the labels. The graph attention network uses

    更新日期:2020-03-27
  • Word2Vec: Optimal Hyper-Parameters and Their Impact on NLP Downstream Tasks
    arXiv.cs.CL Pub Date : 2020-03-23
    Tosin P. Adewumi; Foteini Liwicki; Marcus Liwicki

    Word2Vec is a prominent tool for Natural Language Processing (NLP) tasks. Similar inspiration is found in distributed embeddings for state-of-the-art (sota) deep neural networks. However, wrong combination of hyper-parameters can produce poor quality vectors. The objective of this work is to show optimal combination of hyper-parameters exists and evaluate various combinations. We compare them with

    更新日期:2020-03-27
  • Common-Knowledge Concept Recognition for SEVA
    arXiv.cs.CL Pub Date : 2020-03-26
    Jitin Krishnan; Patrick Coronado; Hemant Purohit; Huzefa Rangwala

    We build a common-knowledge concept recognition system for a Systems Engineer's Virtual Assistant (SEVA) which can be used for downstream tasks such as relation extraction, knowledge graph construction, and question-answering. The problem is formulated as a token classification task similar to named entity extraction. With the help of a domain expert and text processing methods, we construct a dataset

    更新日期:2020-03-27
  • Rat big, cat eaten! Ideas for a useful deep-agent protolanguage
    arXiv.cs.CL Pub Date : 2020-03-17
    Marco Baroni

    Deep-agent communities developing their own language-like communication protocol are a hot (or at least warm) topic in AI. Such agents could be very useful in machine-machine and human-machine interaction scenarios long before they have evolved a protocol as complex as human language. Here, I propose a small set of priorities we should focus on, if we want to get as fast as possible to a stage where

    更新日期:2020-03-27
  • TLDR: Token Loss Dynamic Reweighting for Reducing Repetitive Utterance Generation
    arXiv.cs.CL Pub Date : 2020-03-26
    Shaojie Jiang; Thomas Wolf; Christof Monz; Maarten de Rijke

    Natural Language Generation (NLG) models are prone to generating repetitive utterances. In this work, we study the repetition problem for encoder-decoder models, using both recurrent neural network (RNN) and transformer architectures. To this end, we consider the chit-chat task, where the problem is more prominent than in other tasks that need encoder-decoder architectures. We first study the influence

    更新日期:2020-03-27
  • Towards Making the Most of BERT in Neural Machine Translation
    arXiv.cs.CL Pub Date : 2019-08-15
    Jiacheng Yang; Mingxuan Wang; Hao Zhou; Chengqi Zhao; Yong Yu; Weinan Zhang; Lei Li

    GPT-2 and BERT demonstrate the effectiveness of using pre-trained language models (LMs) on various natural language processing tasks. However, LM fine-tuning often suffers from catastrophic forgetting when applied to resource-rich tasks. In this work, we introduce a concerted training framework (\method) that is the key to integrate the pre-trained LMs to neural machine translation (NMT). Our proposed

    更新日期:2020-03-27
  • Enhancing Out-Of-Domain Utterance Detection with Data Augmentation Based on Word Embeddings
    arXiv.cs.CL Pub Date : 2019-11-24
    Yueqi Feng; Jiali Lin

    For most intelligent assistant systems, it is essential to have a mechanism that detects out-of-domain (OOD) utterances automatically to handle noisy input properly. One typical approach would be introducing a separate class that contains OOD utterance examples combined with in-domain text samples into the classifier. However, since OOD utterances are usually unseen to the training datasets, the detection

    更新日期:2020-03-27
  • Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales
    Int. J. Comput. Vis. (IF 6.071) Pub Date : 2020-03-26
    James Pritts, Zuzana Kukelova, Viktor Larsson, Yaroslava Lochman, Ondřej Chum

    Abstract This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from the image of rigidly-transformed coplanar features. The solvers work on scenes without straight lines and, in general, relax strong assumptions about scene content made by the state of the art. The proposed solvers use the affine invariant that coplanar repeats have the same

    更新日期:2020-03-27
  • Enhanced Balanced Min Cut
    Int. J. Comput. Vis. (IF 6.071) Pub Date : 2020-03-26
    Xiaojun Chen, Weijun Hong, Feiping Nie, Joshua Zhexue Huang, Li Shen

    Abstract Spectral clustering is a hot topic and many spectral clustering algorithms have been proposed. These algorithms usually solve the discrete cluster indicator matrix by relaxing the original problems, obtaining the continuous solution and finally obtaining a discrete solution that is close to the continuous solution. However, such methods often result in a non-optimal solution to the original

    更新日期:2020-03-27
  • Automated crack evaluation of a high‐rise bridge pier using a ring‐type climbing robot
    Comput. Aided Civ. Infrastruct. Eng. (IF 6.208) Pub Date : 2020-03-26
    Keunyoung Jang; Yun‐Kyu An; Byunghyun Kim; Soojin Cho

    This article proposes a deep learning‐based automated crack evaluation technique for a high‐rise bridge pier using a ring‐type climbing robot. First, a ring‐type climbing robot system composed of multiple vision cameras, climbing robot, and control computer is developed. By spatially moving the climbing robot system along a target bridge pier with close‐up scanning condition, high‐quality raw vision

    更新日期:2020-03-27
  • Three-dimensional active earth pressure under transient unsaturated flow conditions
    Comput. Geotech. (IF 3.345) Pub Date : 2020-03-26
    Zheng-Wei Li; Xiao-Li Yang

    The active earth pressure evaluation was typically conducted assuming dry backfills and/or two-dimensional collapse mechanisms. In practice, retained slope collapse usually shows a three-dimensional (3D) feature and soils are usually unsaturated. The present work develops a framework for evaluating the 3D active earth pressure under transient unsaturated flow conditions. The framework is implemented

    更新日期:2020-03-27
  • Table of Contents
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2020-03-24

    Presents the table of contents for this issue of the publication.

    更新日期:2020-03-27
  • IEEE Transactions on Multimedia
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2020-03-24

    Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

    更新日期:2020-03-27
  • Fast Depth and Inter Mode Prediction for Quality Scalable High Efficiency Video Coding
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-23
    Dayong Wang; Yu Sun; Ce Zhu; Weisheng Li; Frederic Dufaux

    The scalable high efficiency video coding (SHVC) is an extension of high efficiency video coding (HEVC). It introduces multiple layers and inter-layer prediction, thus significantly increases the coding complexity on top of the already complicated HEVC encoder. In inter prediction for quality SHVC, in order to determine the best possible mode at each depth level, a coding tree unit can be recursively

    更新日期:2020-03-27
  • Content-Based Light Field Image Compression Method With Gaussian Process Regression
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-09
    Deyang Liu; Ping An; Ran Ma; Wenfa Zhan; Xinpeng Huang; Ali Abdullah Yahya

    Light field (LF) imaging enables new possibilities for digital imaging, such as digital refocusing, changing of focus plane, changing of viewpoint, scene-depth estimation, and 3D scene reconstruction, by capturing both spatial and angular information of light rays. However, one main problem in dealing with LF data is its sheer volume. In this context, efficient compression methods are needed for such

    更新日期:2020-03-27
  • Energy Compaction-Based Image Compression Using Convolutional AutoEncoder
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-29
    Zhengxue Cheng; Heming Sun; Masaru Takeuchi; Jiro Katto

    Image compression has been an important research topic for many decades. Recently, deep learning has achieved great success in many computer vision tasks, and its use in image compression has gradually been increasing. In this paper, we present an energy compaction-based image compression architecture using a convolutional autoencoder (CAE) to achieve high coding efficiency. Our main contributions

    更新日期:2020-03-27
  • Reversible Data Hiding in Encrypted Images Based on Multi-MSB Prediction and Huffman Coding
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-20
    Zhaoxia Yin; Youzhi Xiang; Xinpeng Zhang

    With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) has attracted increasing attention as a technology that can: embed additional data in the image encryption domain, ensure that the embedded data can be extracted error-free, and the original image can be restored losslessly. In this paper, a high-capacity RDHEI algorithm based on multi-MSB

    更新日期:2020-03-27
  • Saliency Detection via a Multiple Self-Weighted Graph-Based Manifold Ranking
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-14
    Cheng Deng; Xu Yang; Feiping Nie; Dapeng Tao

    As an important task in the process of image understanding and analysis, saliency detection has recently received increasing attention. In this paper, we propose an efficient multiple self-weighted graph-based manifold ranking method to construct salient maps. First, we extract several different views of features from superpixels, and generate original salient regions as foreground and background cues

    更新日期:2020-03-27
  • Enhancing the Quality of Image Tagging Using a Visio-Textual Knowledge Base
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-23
    Chandramani Chaudhary; Poonam Goyal; Dhanashree Nellayi Prasad; Yi-Ping Phoebe Chen

    Auto-tagging of images is important for image understanding and for tag-based applications viz. image retrieval, visual question-answering, image captioning, etc. Although existing tagging methods incorporate both visual and textual information to assign/refine tags, they lag in tag-image relevance, completeness, and preciseness, thereby resulting in the unsatisfactory performance of tag-based applications

    更新日期:2020-03-27
  • Kernelized Fuzzy Modal Variation for Local Change Detection From Video Scenes
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-29
    Badri Narayan Subudhi; Thangaraj Veerakumar; S. Esakkirajan; Ashish Ghosh

    Background subtraction (BGS) is a popular scheme epitomized in the state-of-the-art literature on video processing. In this context, a novel online kernelized fuzzy modal variation based background subtraction scheme for detecting local changes from the sequences of image frames is proposed. In the proposed scheme, the time varying background at different instances of time are modeled using fuzzy set

    更新日期:2020-03-27
  • Vibrotactile Quality Assessment: Hybrid Metric Design Based on SNR and SSIM
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-20
    Xun Liu; Mischa Dohler; Yansha Deng

    The emerging mulsemedia (MULtiple SEnsorial MEDIA) introduces new sensorial data (haptic, olfaction, gustation, etc.), significantly augmenting the conventional audio-visual communication. This can be used in many areas, such as immersive entertainment and innovative education. Previous research has been dedicated to evaluating the impact of other sensorial data on conventional multimedia; however

    更新日期:2020-03-27
  • Audio–Visual Particle Flow SMC-PHD Filtering for Multi-Speaker Tracking
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-23
    Yang Liu; Volkan Kılıç; Jian Guan; Wenwu Wang

    Sequential Monte Carlo probability hypothesis density (SMC-PHD) filtering is a popular method used recently for audio-visual (AV) multi-speaker tracking. However, due to the weight degeneracy problem, the posterior distribution can be represented poorly by the estimated probability, when only a few particles are present around the peak of the likelihood density function. To address this issue, we propose

    更新日期:2020-03-27
  • An EEG-Based Study on Perception of Video Distortion Under Various Content Motion Conditions
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-09
    Xiwen Liu; Xiaoming Tao; Mai Xu; Yafeng Zhan; Jianhua Lu

    Human perception sensitivity to video distortion is vital for visual quality assessment (VQA). Different from the perception mechanism of image distortion that has been thoroughly studied, the perception of video distortion is inevitably influenced by motion of dynamic content due to the characteristics of the human visual system (HVS). In this paper, electroencephalography (EEG) is used as a novel

    更新日期:2020-03-27
  • Training Objective Image and Video Quality Estimators Using Multiple Databases
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-15
    Lukáš Krasula; Yoann Baveye; Patrick Le Callet

    Machine learning (ML) is an essential part of recent advances in computer science. To fully exploit its potential, ML-based algorithms require a considerable amount of annotated data to be used for training. This represents a severe limitation in the field of image and video quality assessment since obtaining large-scale annotated databases is time-consuming and expensive. Moreover, the resulting quality

    更新日期:2020-03-27
  • Learning the Traditional Art of Chinese Calligraphy via Three-Dimensional Reconstruction and Assessment
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-23
    Muwei Jian; Junyu Dong; Maoguo Gong; Hui Yu; Liqiang Nie; Yilong Yin; Kin-Man Lam

    The traditional art of Chinese calligraphy, reflecting the wisdom of the grass-roots community, is the soul of Chinese culture. Just like many other types of craftsmanship, it is part of the historical heritage and is worth conserving, from generation to generation. Since the movements of an ink brush are in a 3D style when Chinese calligraphy is written, they embody “The Power of Beauty,” comprising

    更新日期:2020-03-27
  • Flexibly Connectable Light Field System For Free View Exploration
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-12
    Hyunmin Jung; Hyuk-Jae Lee; Chae Eun Rhee

    Conventional captured-image-based virtual reality (VR) systems have three degrees of freedom (DoFs), where only rotational user motion is tracked for view rendering. This is a major cause of the reduced sense of reality. To increase user immersion levels akin to the real world, 3-DoF+ VR systems that support not only rotational but also translational view changes have been proposed. The light-field

    更新日期:2020-03-27
  • Compact Hash Code Learning With Binary Deep Neural Network
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-15
    Thanh-Toan Do; Tuan Hoang; Dang-Khoa Le Tan; Anh-Dzung Doan; Ngai-Man Cheung

    Learning compact binary codes for image retrieval problem using deep neural networks has recently attracted increasing attention. However, training deep hashing networks is challenging due to the binary constraints on the hash codes. In this paper, we propose deep network models and learning algorithms for learning binary hash codes given image representations under both unsupervised and supervised

    更新日期:2020-03-27
  • Multi-Party WebRTC Services Using Delay and Bandwidth Aware SDN-Assisted IP Multicasting of Scalable Video Over 5G Networks
    IEEE Trans. Multimedia (IF 5.452) Pub Date : 2019-08-23
    Riza Arda Kirmizioglu; A. Murat Tekalp

    At present, multi-party WebRTC videoconferencing between peers with heterogenous network resources and terminals is enabled over the best-effort Internet using a central selective forwarding unit (SFU), where each peer sends a scalable encoded video stream to the SFU. This connection model avoids the upload bandwidth bottleneck associated with mesh connections; however, it increases peer delay and

    更新日期:2020-03-27
Contents have been reproduced by permission of the publishers.
导出
全部期刊列表>>
全球疫情及响应:BMC Medicine专题征稿
欢迎探索2019年最具下载量的化学论文
新版X-MOL期刊搜索和高级搜索功能介绍
化学材料学全球高引用
ACS材料视界
南方科技大学
x-mol收录
南方科技大学
自然科研论文编辑服务
上海交通大学彭文杰
中国科学院长春应化所于聪-4-8
武汉工程大学
课题组网站
X-MOL
深圳大学二维材料实验室张晗
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug