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Communications in computer and Information science 2020年 1219 CCIS卷 v-vi页

作者： Ziefle, Martina Maciaszek, Leszek A. Human-Computer Interaction Center RWTH Aachen University AachenNordrhein-Westfalen Germany Institute of Business Informatics Wroclaw University of Economics Wroclaw Poland Department of Computing Macquarie University SydneyNSW Australia

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GazeGAN: A robust generative adversarial saliency model based on invariance analysis of human gaze during scene free viewing

arXiv

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arXiv 2019年

作者： Che, Zhaohui Borji, Ali Zhai, Guangtao Min, Xiongkuo Guo, Guodong Le Callet, Patrick Institute of Image Communication and Network Engineering Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai200240 China MarkableAI United States Institute of Deep Learning Baidu Research Department of Computer Science and Electrical Engineering West Virginia University MorgantownWV United States Equipe Image Perception et Interaction Laboratoire des Sciences du Numérique de Nantes Université de Nantes France

—Data size is the bottleneck for developing deep saliency models, because collecting eye-movement data is very time-consuming and expensive. Most of current studies on human attention and saliency modeling have used high-quality stereotype stimuli. In real world, however, captured images undergo various types of transformations. Can we use these transformations to augment existing saliency datasets? Here, we first create a novel saliency dataset including fixations of 10 observers over 1900 images degraded by 19 types of transformations. Second, by analyzing eye movements, we find that observers look at different locations over transformed versus original images. Third, we utilize the new data over transformed images, called data augmentation transformation (DAT), to train deep saliency models. We find that label-preserving DATs with negligible impact on human gaze boost saliency prediction, whereas some other DATs that severely impact human gaze degrade the performance. These label-preserving valid augmentation transformations provide a solution to enlarge existing saliency datasets. Finally, we introduce a novel saliency model based on generative adversarial network (dubbed GazeGAN). A modified U-Net is proposed as the generator of the GazeGAN, which combines classic "skip connections" with a novel "center-surround connection (CSC)", in order to leverage multi-level features. We also propose a histogram loss based on Alternative Chi-Square Distance (ACS HistLoss) to refine the saliency map in terms of luminance distribution. Extensive experiments and comparisons over 3 datasets indicate that GazeGAN achieves the best performance in terms of popular saliency evaluation metrics, and is more robust to various perturbations. We also provide a comprehensive quantitative comparison of 22 state-of-the-art saliency models on distorted images, which contributes a robustness benchmark for saliency community. Our code and data are available at: https://***/CZHQuality/

关键词： Luminance

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Spiral-Phased Laguerre-Gaussian Modes Generation in SWDM over Few Mode Fiber based on Electrical Equalization

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Journal of Physics: Conference Series 2020年第2期1529卷

作者： Alaan Ghazi Alaa Fareed Tendai Masunda S. A. Aljunid Syed Zulkarnain Syed Idrus Angela Amphawan Aras Al-dawoodi C. B. M Rashidi Ibrahim Eskandar Ibrahim Fadhel School of Human Development & Techno-communication Universiti Malaysia Perlis Malaysia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Computer Technical Engineering Alkitab University Iraq School of Computing Universiti Utara Malaysia Malaysia Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts USA Computer Science Department College of Computer Science and Information Technology Kirkuk University Iraq Department of Computer and Information Systems National Institute of Administrative Science Yemen

Space division multiplexing, in conjunction with wavelength division multiplexing, is a powerful mechanism that increases spatial channels significantly in a single optical fiber. Spiral Phased-Laguerre-Gaussian (SP-LG) modes indicate that they effectively reduce mode coupling, thereby increasing the channel response and performance positively. However, mode-coupling influence optical fiber system leads to inter-symbol interference (ISI) between the channels and reduces both capacity and distance. In this paper, we apply the SP-LG modes in a space wavelength division multiplexing over a few-mode fiber system. The results demonstrate significant improvements in reducing channels effects and ISI. The performance evaluations are based on the bit-error-rate (BER), eye diagram and spectrum analyzer.

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Tablet-based strength-balance training to motivate and improve adherence to exercise in independently living older people: Part 2 of a phase ii preclinical exploratory trial

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Journal of Medical Internet Research 2014年第6期16卷 e159页

作者： Van Het Reve, Eva Silveira, Patrícia Daniel, Florian Casati, Fabio De Bruin, Eling D. Institute of Human Movement Sciences and Sport Department of Health Sciences and Technology ETH Zurich Zurich 8093 Wolfgang-Pauli-Strasse 27 Switzerland University of Trento Department of Information Engineering and Computer Science Trento Italy CAPHRI School for Public Health and Primary Care Department of Epidemiology Maastricht University Maastricht Netherlands Centre for Evidence Based Physiotherapy Maastricht University Maastricht Netherlands

Home-based exercise programs can improve physical functioning and health status of elderly people. Successful implementation of exercise interventions for older people presents major challenges and supporting elderly people properly while doing their home-based exercises is essential for training success. We developed a tablet-based system-ActiveLifestyle-that offers older adults a home-based strength-balance training program with incorporated motivation strategies and support features. Objective: The goal was to compare 3 different home-based training programs with respect to their effect on measures of gait quality and physical performance through planned comparisons between (1) tablet-based and brochure-based interventions, (2) individual and social motivation strategies, and (3) active and inactive participants. Methods: A total of 44 autonomous-living elderly people (mean 75, SD 6 years) were assigned to 3 training groups: social (tablet guided, n=14), individual (tablet guided, n=13), and brochure (brochure guided, n=17). All groups joined a 12-week progressive home-based strength-balance training program. Outcome measures were gait performance under single and dual task conditions, dual task costs of walking, falls efficacy, and physical performance as measured by the Short Physical Performance Battery (SPPB). Furthermore, active (≥75% program compliance) and inactive (<75% program compliance) individuals were compared based on their characteristics and outcome measures. Results: The tablet groups showed significant improvements in single and dual task walking, whereas there were no significant changes observable in the brochure group. Between-groups comparisons revealed significant differences for gait velocity (U=138.5;P=.03, r=.33) and cadence (U=138.5, P=.03 r=.34) during dual task walking at preferred speed in favor of the tablet groups. The brochure group had more inactive participants, but this did not reach statistical significance (U=167, P=.06, r=.2

关键词： Aging Delivery of health care Exercise therapy Gait Tablet

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A Systematic review of Multi-Mode Fiber based on Dimensional Code in Optical-CDMA

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Journal of Physics: Conference Series 2021年第1期1860卷

作者： Alaan Ghazi S.A. Aljunid Syed Zulkarnain Syed Idrus C.B.M Rashidi Aras Al-dawoodi Baban A. Mahmood Alaa Fareed Mohammed U. Zaenal Nameer Hashim Qasim Ranjdr M. Rafeeq Faculty of Applied and Human Sciences University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Technical Engineering Al-Qalam university College Iraq Computer Science Department College of Computer Science and Information Technology Kirkuk University Kirkuk Iraq School of Computing University Utara Malaysia Malaysia

This paper deals with optical code division multiple access (optical-CDMA) and provides a general analysis of multi-mode fiber (MMF). The purpose of this work is to classify the works in the literature that are related to Optical-CDMA based on MMF and to find the limitation of the researches done in this field. Several challenges that occur in the medium such as multiple-access interference (MAI), pulse dispersion (PD) and nonlinearity in optical fibers deteriorate system performances and become a major performance-limiting factor.

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R2 Indicator and Deep Reinforcement Learning Enhanced Adaptive Multi-Objective Evolutionary Algorithm

arXiv

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arXiv 2024年

作者： Tahernezhad-Javazm, Farajollah Rankin, Debbie Bois, Naomi Du Smith, Alice E. Coyle, Damien Intelligent Systems Research Center School of Computing Engineering and Intelligent Systems Ulster University LondonderryBT48 7JL United Kingdom The Bath Institute for Augmented Human University of Bath BathBA2 7AY United Kingdom The Department of Industrial and Systems Engineering Department of Computer Science and Software Engineering Auburn University AuburnAL36849 United States

Choosing an appropriate optimization algorithm is essential to achieving success in optimization challenges. Here we present a new evolutionary algorithm structure that utilizes a reinforcement learning-based agent aimed at addressing these issues. The agent employs a double deep q-network to choose a specific evolutionary operator based on feedback it receives from the environment during optimization. The algorithm’s structure contains five single-objective evolutionary algorithm operators. This single-objective structure is transformed into a multi-objective one using the R2 indicator. This indicator serves two purposes within our structure: first, it renders the algorithm multi-objective, and second, provides a means to evaluate each algorithm’s performance in each generation to facilitate constructing the reinforcement learning-based reward function. The proposed R2-reinforcement learning multi-objective evolutionary algorithm (R2-RLMOEA) is compared with six other multiobjective algorithms that are based on R2 indicators. These six algorithms include the operators used in R2-RLMOEA as well as an R2 indicator-based algorithm that randomly selects operators during optimization. We benchmark performance using the CEC09 functions, with performance measured by inverted generational distance and spacing. The R2-RLMOEA algorithm outperforms all other algorithms with strong statistical significance (p © 2024, CC BY.

关键词： Reinforcement learning

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AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Shahzad, Sahibzada Adil Hashmi, Ammarah Peng, Yan-Tsung Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Multimodal manipulations (also known as audiovisual deepfakes) make it difficult for unimodal deepfake detectors to detect forgeries in multimedia content. To avoid the spread of false propaganda and fake news, timely detection is crucial. The damage to either modality (i.e., visual or audio) can only be discovered through multi-modal models that can exploit both pieces of information simultaneously. Previous methods mainly adopt uni-modal video forensics and use supervised pre-training for forgery detection. This study proposes a new method based on a multi-modal self-supervised-learning (SSL) feature extractor to exploit inconsistency between audio and visual modalities for multi-modal video forgery detection. We use the transformer-based SSL pre-trained Audio-Visual HuBERT (AV-HuBERT) model as a visual and acoustic feature extractor and a multi-scale temporal convolutional neural network to capture the temporal correlation between the audio and visual modalities. Since AV-HuBERT only extracts visual features from the lip region, we also adopt another transformer-based video model to exploit facial features and capture spatial and temporal artifacts caused during the deepfake generation process. Experimental results show that our model outperforms all existing models and achieves new state-of-the-art performance on the FakeAVCeleb and DeepfakeTIMIT datasets. © 2023, CC BY.

关键词： Audio acoustics

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Time-varying cortical connectivity by adaptive multivariate estimators applied to a combined foot-lips movement

Time-varying cortical connectivity by adaptive multivariate ...

引用

29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), vol.11

作者： L. Astolfi F. Cincotti D. Mattia F. De Vico Fallani A. Colosimo S. Salinari M. G. Marciani M. Ursino M. Zavaglia W. Hesse H. Witte F. Babiloni Department of Computer Science University of Rome La Sapienza and IRCCS Fondazione Santa Lucia Rome Italy Fondazione Santa Lucia IRCCS Rome Italy Centro di Ricerca de La Sapienza per l'Analisi dei Modelli e dell'Informazione nei Sistemi Biomedici Rome Italy Department of Neuroscience Fondazione Santa Lucia University of Roma Tor Vergata Rome Italy DEIS University of Bologna Bologna Italy Institute of Medical Statistics Computer Sciences and Documentation Friedrich-Schiller-Universitat Jena Germany Department of Human Physiology and Pharmacology of the University of Rome La Sapienza and IRCCS Fondazione Santa Lucia Rome Italy

In this paper we propose the use of an adaptive multivariate approach to define time-varying multivariate estimators based on the Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC). DTF and PDC are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. Time-varying DTF and PDC were obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs. Such estimators are able to follow rapid changes in the connectivity between cortical areas during an experimental task. We provide an application to the cortical estimations obtained from high resolution EEG data, recorded from a group of healthy subject during a combined foot-lips movement, and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected, one constant across the task and the other evolving during the preparation of the joint movement.

关键词： Electroencephalography Signal processing algorithms Transfer functions Coherence Brain modeling Resonance light scattering Neuroscience humans Physiology computer science

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Erratum to: Effective session key distribution for secure fast handover in mobile networks

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Telecommunication Systems 2009年第1期52卷 359-359页

作者： Park, Jong Hyuk Jin, Qun Department of Computer Science and Engineering Seoul National University of Technology Seoul Korea Department of Human Informatics and Cognitive Sciences Waseda University Saitama Japan

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Revisiting Lesion Tracking in 3D Total Body Photography

arXiv

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arXiv 2024年

作者： Huang, Wei-Lun Xue, Minghao Liu, Zhiyou Tashayyod, Davood Kang, Jun Gandjbakhche, Amir Kazhdan, Misha Armand, Mehran Johns Hopkins University Whiting School of Engineering Department of Computer Science BaltimoreMD United States Johns Hopkins School of Medicine Department of Dermatology BaltimoreMD United States University of Arkansas Institute for Integrative and Innovative Research Department of Mechanical Engineering AR United States Eunice Kennedy Shriver National Institute of Child Health and Human Development BethesdaMD United States Lumo Imaging RockvilleMD United States

Melanoma is the most deadly form of skin cancer. Tracking the evolution of nevi and detecting new lesions across the body is essential for the early detection of melanoma. Despite prior work on longitudinal tracking of skin lesions in 3D total body photography, there are still several challenges, including 1) low accuracy for finding correct lesion pairs across scans, 2) sensitivity to noisy lesion detection, and 3) lack of large-scale datasets with numerous annotated lesion pairs. We propose a framework that takes in a pair of 3D textured meshes, matches lesions in the context of total body photography, and identifies unmatchable lesions. We start by computing correspondence maps bringing the source and target meshes to a template mesh. Using these maps to define source/target signals over the template domain, we construct a flow field aligning the mapped signals. The initial correspondence maps are then refined by advecting forward/backward along the vector field. Finally, lesion assignment is performed using the refined correspondence maps. We propose the first large-scale dataset for skin lesion tracking with 25K lesion pairs across 198 subjects. The proposed method achieves a success rate of 89.9 % (at 10 mm criterion) for all pairs of annotated lesions and a matching accuracy of 98.2% for subjects with more than 200 lesions. Copyright © 2024, The Authors. All rights reserved.

关键词： Mesh generation

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