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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Wang, Ye Shan, Gongbing Li, Hua Feng, Ruliang Zhang, Yilan Li, Guanglin Wang, Lin CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macau Joint Laboratory of Human-Machine Intelligence-Synergy Systems Guangdong Shenzhen518055 China University of Lethbridge Department of Mathematics and Computer Science LethbridgeABABT1K3M4 Canada Department of Kinesiology and Physical Education University of Lethbridge LethbridgeABT1K3M4 Canada

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Real-Time biomechanical feedback can provide direct and objective quantified information for any practitioners, such as the athletes/coaches, to assist in accelerating their motor skills' learning and training process. However, it is usually difficult to monitor the human motion in full and acquire the key biomechanical parameters (i.e., the kinematic and kinetic data, the EMG, etc.) just with few sensors in some elite sports involving fast movements and complex motor skills. Using too many sensors in the field tests may limit the athletes' motor ability and affect the collected data's validity and reliability. In this paper, we employ a deep learning method to immensely reduce the number of sensors required for providing the real-Time biomechanical feedback in field, according to the hammer-Throw local motion features found from our pilot study. Based on the Keras API imported from the TensorFlow open-source platform, two Sequential Neural Network models are implemented and compared. One model has two inputs (i.e., vertical displacements and velocities on waist) and six outputs (i.e., vital joint angles on lower limbs). The other one has four inputs (i.e., vertical displacements and velocities on wrist and waist) and thirteen outputs (i.e., vital joint angles on both upper and lower limbs). The experimental results demonstrate that the vital joint angles on the upper and lower limbs have strong correlation with the vertical wrist and waist/hip displacements respectively. This study indicates that fewer wearable sensors can be applied in fast and complex movements to obtain the most significant kinematic data, whereas more biomechanical parameters can be further gained by prediction. © 2022 IEEE.

关键词： Kinematics

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Gaia Net: Towards robust spectroscopic parameters of stars of all evolutionary stages

arXiv

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arXiv 2025年

作者： Huson, Dylan Cowan, Indiana Sizemore, Logan Kounkel, Marina Hutchinson, Brian Computer Science Department Western Washington University 516 High Street BellinghamWA98225 United States Department of Physics and Astronomy University of North Florida 1 UNF Dr JacksonvilleFL32224 United States Human-Earth Systems & Science Group Pacific Northwest National Laboratory 5825 University Research Court Suite 3500 College ParkMD20740 United States

We present a new processing of XP spectra for 220 million stars released in Gaia DR3. The new data model is capable of handling objects with Teff between 2000 and 50,000 K, and with log g between 0 and 10, including objects of multitude of masses and evolutionary stages. This includes for the first time ever robust processing of spectroscopic parameters for pre-main sequence stars, with log g sensitivity towards their age. Through this analysis we examine the distribution of young low mass stars with ages of up to 20 Myr in the solar neighborhood, and we identify a new massive (> 1000 stars) population, Ophion, which is found east of Sco Cen. This population appears to be fully disrupted, with negligible kinematic coherence. Nonetheless, due its young age it appears to still persist as a spacial overdensity. Through improved determination of ages of the nearby stars, it may be possible to better recover star forming history of the solar neighborhood outside of the moving groups. © 2025, CC BY.

关键词： Giant stars

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Advances and challenges in unsupervised neural machine translation 16

Advances and challenges in unsupervised neural machine trans...

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16th Conference of the European Chapter of the Associationfor Computational Linguistics: Tutorials, EACL 2021

作者： Wang, Rui Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781954085039

Unsupervised cross-lingual language representation initialization methods, together with mechanisms such as denoising and back-translation, have advanced unsupervised neural machine translation (UNMT), which has achieved impressive results. Meanwhile, there are still several challenges for UNMT. This tutorial first introduces the background and the latest progress of UNMT. We then examine a number of challenges to UNMT and give empirical results on how well the technology currently holds up1 © 2020 Association for Computational Linguistics.

关键词： Neural machine translation

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Gesture interaction in virtual reality

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Virtual Reality & Intelligent Hardware 2019年第1期1卷 84-112页

作者： Yang LI Jin HUANG Feng TIAN Hong-An WANG Guo-Zhong DAI Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of SciencesBeijing 100190China State Key Laboratory of Computer Science Chinese Academy of SciencesBeijing 100190China

With the development of virtual reality(VR)and human-computer interaction technology,how to use natural and efficient interaction methods in the virtual environment has become a hot topic of *** is one of the most important communication methods of human beings,which can effectively express users'*** the past few decades,gesture-based interaction has made significant *** article focuses on the gesture interaction technology and discusses the definition and classification of gestures,input devices for gesture interaction,and gesture interaction recognition *** application of gesture interaction technology in virtual reality is studied,the existing problems in the current gesture interaction are summarized,and the future development is prospected.

关键词： Virtual reality Gesture interaction Gesture recognition

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Prediction of chilling damage risk in maize growth period based on probabilistic neural network approach

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International Journal of Agricultural and Biological Engineering 2021年第2期14卷 120-125页

作者： Chunqiao Mi Changhua Zhao Qingyou Deng Xiaowu Deng School of Computer Science and Engineering Huaihua UniversityHuaihua 418000HunanChina Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture Huaihua 418000HunanChina Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua 418000HunanChina Human Resource Department Huaihua UniversityHuaihua 418000HunanChina

Low temperature chilling damage is one of the most serious disasters in maize production,which is a typical non-linear complex issue with numerous influencing factors and strong *** to predict it is not only a hot theoretical research topic,but also an urgent practical problem to be ***,most of the current researches are focusing on post-disaster static descriptive assessment rather than pre-disaster dynamic predictive analysis,resulting in the problems such as no indicative result and low *** this study,the satisfaction rate of environmental accumulated temperature for maize production was used to measure the chilling damage risk,and a model for maize chilling damage risk prediction based on probabilistic neural network was *** model was composed of input layer,pattern layer,summation layer and output *** obtained results showed that the prediction accuracy for the most serious risk level was as high as 0.91,and the rates of the Type I Error and Type II Error made by the model were 0.1 and 0.09,*** indicated that the model employed was promising with good *** results of this research are of both theoretical significance for providing a new reference method of pre-disaster prediction to study maize chilling disaster risk and practical significance for reducing maize production risk and ensuring yield safety.

关键词： maize chilling damage risk prediction probabilistic neural network

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From EEG to Eye Movements: Cross-modal Emotion Recognition Using Constrained Adversarial Network with Dual Attention

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IEEE Transactions on Affective Computing 2024年

作者： Wang, Yiting Liu, Jia-Wen Lu, Bao-Liang Zheng, Wei-Long Karolinska Institutet Department of Clinical Neuroscience Stockholm171 77 Sweden Shanghai Jiao Tong University China Shanghai Jiao Tong University Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai200240 China Shanghai Jiao Tong University School of Medicine RuiJin-Mihoyo Laboratory Clinical Neuroscience Center RuiJin Hospital Shanghai200020 China Shanghai Emotionhelper Technology Co. Ltd. Shanghai China

Emotion recognition is a fundamental part of affective computing, obtaining performance gain from multimodal methods. Electroencephalography (EEG) and eye movements are extensively used as they contain complementary information. However, the inconvenient acquisition of EEG is hindering the extensive adoption of multimodal emotion recognition in daily applications while eye movements are more convenient to collect but with lower performance. To tackle this issue, we propose a Constrained Adversarial Network with Dual Attention (CANDA), exploiting the complementary information from multiple modalities during training to improve the test-time performance of single easily acquired modality, i.e., transferring knowledge from a stronger modality to a weaker modality. During training, a common joint space is learned to diminish the distribution discrepancy among different modalities and incorporate the multimodal representations. During test, single modality is converted to the common space achieving comparable performance to multiple modalities. Extensive experiments demonstrate that our model achieves the state-of-the-art performance for cross-modal emotion recognition. Specifically, the mean accuracy increases around 15% on SEED, 15% on SEED-IV, and 2% on SEED-V compared to the latest baseline for emotion recognition. Visualization of features in the joint space illustrates that the distribution of different modalities aligns together with the discriminative ability regarding various emotions. © 2010-2012 IEEE.

关键词： Electroencephalography

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Genetic evidence for facial variation being a composite phenotype of cranial variation and facial soft tissue thickness

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Journal of Genetics and Genomics 2022年第10期49卷 934-942页

作者： Wei Qian Manfei Zhang Kaiwen Wan Yunxia Xie Siyuan Du Jiarui Li Xiongzheng Mu Jiange Qiu Xiangyang Xue Xiahai Zhuang Yingzhi Wu Fan Liu Sijia Wang State Key Laboratory of Genetic Engineering Human Phenome InstituteZhangjiang Fudan International Innovation CenterFudan UniversityShanghai 201203China School of Computer Science Fudan UniversityShanghai 200438China CAS Key Laboratory of Computational Biology Shanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China School of Data Science Fudan UniversityShanghai 200433China Academy of Medical Science Zhengzhou UniversityZhengzhouHenan 450052China Department of Plastic Surgery Huashan HospitalFudan UniversityShanghai 200040China CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsUniversity of Chinese Academy of SciencesBeijing 100101China School of Future Technology University of Chinese Academy of SciencesBeijing 101408China Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunmingYunnan 650223China

Facial and cranial variation represent a multidimensional set of highly correlated and heritable *** is known about the genetic basis explaining this *** develop a software package ALo SFL for simultaneous localization of facial and cranial landmarks from head computed tomography(CT)images,apply it in the analysis of head CT images of 777 Han Chinese women,and obtain a set of phenotypes representing variation in face,skull and facial soft tissue thickness(FSTT).Association analysis of 301 single nucleotide polymorphisms(SNPs)from 191 distinct genomic loci previously associated with facial variation reveals an unexpected larger number of loci showing significant associations(P<1e-3)with cranial phenotypes than expected under the null(O/E=3.39),suggesting facial and cranial phenotypes share a substantial proportion of genetic *** FSTT to a SNP-only model shows a large impact in explaining facial variance.A gene ontology analysis reveals that bone morphogenesis and osteoblast differentiation likely underlie our cranial-significant ***,this study simultaneously investigates the genetic effects on both facial and cranial variation of the same sample,supporting that facial variation is a composite phenotype of cranial variation and FSTT.

关键词： Facial variation Cranial variation Association analysis Single nucleotide polymorphism Facial soft tissue thickness Computed tomography

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A Lightweight Model for Perceptual Image Compression via Implicit Priors

arXiv

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arXiv 2025年

作者： Wei, Hao Zhou, Yanhui Jia, Yiwen Ge, Chenyang Anwar, Saeed Mian, Ajmal National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China School of Information and Telecommunication Xi’an Jiaotong University Xi’an710049 China Department of Computer Science and Software Engineering The University of Western Australia Crawley PerthWA6009 Australia

Perceptual image compression has shown strong potential for producing visually appealing results at low bitrates, surpassing classical standards and pixel-wise distortion-oriented neural methods. However, existing methods typically improve compression performance by incorporating explicit semantic priors, such as segmentation maps and textual features, into the encoder or decoder, which increases model complexity by adding parameters and floating-point operations. This limits the model’s practicality, as image compression often occurs on resource-limited mobile devices. To alleviate this problem, we propose a lightweight perceptual Image Compression method using Implicit Semantic Priors (ICISP). We first develop an enhanced visual state space block that exploits local and global spatial dependencies to reduce redundancy. Since different frequency information contributes unequally to compression, we develop a frequency decomposition modulation block to adaptively preserve or reduce the low-frequency and high-frequency information. We establish the above blocks as the main modules of the encoder-decoder, and to further improve the perceptual quality of the reconstructed images, we develop a semantic-informed discriminator that uses implicit semantic priors from a pretrained DINOv2 encoder. Experiments on popular benchmarks show that our method achieves competitive compression performance and has significantly fewer network parameters and floating point operations than the existing state-of-the-art. We will release the code and trained models. Copyright © 2025, The Authors. All rights reserved.

关键词： Decoding

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Camera-Based HRV Prediction for Remote Learning Environments

arXiv

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arXiv 2023年

作者： Wang, Kegang Wei, Yantao Tang, Jiankai Wang, Yuntao Tong, Mingwen Gao, Jie Ma, Yujian Zhao, Zhongjin Central China Normal University Wuhan430079 China National Key Laboratory of Human Factors Engineering Beijing100094 China Department of Computer Science and Technology Tsinghua University Beijing100084 China East China Normal University Shanghai200241 China

In recent years, due to the widespread use of internet videos, remote photoplethysmography (rPPG) has gained more and more attention in the fields of affective computing. Restoring blood volume pulse (BVP) signals from facial videos is a challenging task that involves a series of preprocessing, image algorithms, and postprocessing to restore waveforms. Not only is the heart rate metric utilized for affective computing, but the heart rate variability (HRV) metric is even more significant. The challenge in obtaining HRV indices through rPPG lies in the necessity for algorithms to precisely predict the BVP peak positions. In this paper, we collected the Remote Learning Affect and Physiology (RLAP) dataset, which includes over 32 hours of highly synchronized video and labels from 58 subjects. This is a public dataset whose BVP labels have been meticulously designed to better suit the training of HRV models. Using the RLAP dataset, we trained a new model called Seq-rPPG, it is a model based on one-dimensional convolution, and experimental results reveal that this structure is more suitable for handling HRV tasks, which outperformed all other baselines in HRV performance and also demonstrated significant advantages in computational efficiency. © 2023, CC BY-NC-SA.

关键词： Photoplethysmography

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The understanding of congruent and incongruent referential gaze in 17-month-old infants: an eye-tracking study comparing human and robot (vol 10, pg 11918, 2020)

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SCIENTIFIC REPORTS 2020年第1期10卷 1-10页

作者： Manzi, F. Ishikawa, M. Di Dio, C. Itakura, S. Kanda, T. Ishiguro, H. Massaro, D. Marchetti, A. Research Unit on Theory of Mind Department of Psychology Università Cattolica del Sacro Cuore Milan Italy School of Graduated Letter Department of Psychology Kyoto University Kyoto Japan Centre for Baby Science Doshisha University Kyoto Japan Human-Robot Interaction Laboratory Department of Computer Science Kyoto University Kyoto Japan Advanced Telecommunications Research Institute International IRC/HIL Keihanna Science City Kyoto Japan Department of Systems Innovation Osaka University Toyonaka Japan

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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