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2019 International Conference on Applied and Engineering Mathematics, ICAEM 2019

作者： Shehzed, Ahsan Jalal, Ahmad Kim, Kibum Dept. of Computer Science Air University Islamabad Pakistan Dept. of Human-Computer Interaction Hanyang University Seoul Korea Republic of

ISBN: (纸本)9781728123530

Automated video surveillance addresses people's real-time observation to describe their behaviors and interactions. This paper presents a novel multi-person tracking system for crowd counting and normal/abnormal events detection at indoor/outdoor surveillance environments. The proposed system consists of four modules: people detection, head-torso template extraction, tracking and crowd cluster analysis. Firstly, the system extracts human silhouettes using inverse transform as well as median filter reducing the cost of computing and handling various complex monitoring situations. Secondly, people are detected by their head torso due to less varied and hardly occluded. Thirdly, each person is tracked through consecutive frames using the Kalman filter techniques with Jaccard similarity and normalized cross-correlation. Finally, the template marking is used for crowd counting having cues localization and clustered via Gaussian mapping for normal/abnormal events detection. The experimental results on two challenging datasets of video surveillance such as PETS2009 and UMN crowd analysis datasets demonstrate that the proposed system provides 88.7% and 95.5% in terms of counting accuracy and detection rate. © 2019 IEEE.

关键词： Median filters

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SceneSketcher: Fine-Grained Image Retrieval with Scene Sketches 16th

SceneSketcher: Fine-Grained Image Retrieval with Scene Sketc...

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16th European Conference on computer Vision, ECCV 2020

作者： Liu, Fang Zou, Changqing Deng, Xiaoming Zuo, Ran Lai, Yu-Kun Ma, Cuixia Liu, Yong-Jin Wang, Hongan State Key Laboratory of Computer Science and Beijing Key Lab of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China HMI Laboratory Huawei Technologies Shenzhen China Cardiff University Cardiff United Kingdom Tsinghua University Beijing China

ISBN: (纸本)9783030585280

Sketch-based image retrieval (SBIR) has been a popular research topic in recent years. Existing works concentrate on mapping the visual information of sketches and images to a semantic space at the object level. In this paper, for the first time, we study the fine-grained scene-level SBIR problem which aims at retrieving scene images satisfying the user’s specific requirements via a freehand scene sketch. We propose a graph embedding based method to learn the similarity measurement between images and scene sketches, which models the multi-modal information, including the size and appearance of objects as well as their layout information, in an effective manner. To evaluate our approach, we collect a dataset based on SketchyCOCO and extend the dataset using Coco-stuff. Comprehensive experiments demonstrate the significant potential of the proposed approach on the application of fine-grained scene-level image retrieval. © 2020, Springer Nature Switzerland AG.

关键词： Semantics

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Speech AI for All: Promoting Accessibility, Fairness, Inclusivity, and Equity

Speech AI for All: Promoting Accessibility, Fairness, Inclus...

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2025 CHI Conference on human Factors in Computing Systems, CHI EA 2025

作者： Wu, Shaomei Wenzel, Kimi Li, Jingjin Li, Qisheng Pradhan, Alisha Kushalnagar, Raja Lea, Colin Koenecke, Allison Vogler, Christian Hasegawa-Johnson, Mark Su, Norman Makoto Ratner, Nan Bernstein *** Mountain ViewCA United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States *** SeattleWA United States Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Gallaudet University WashingtonDC United States Apple CupertinoCA United States Cornell University IthacaNY United States Technology Access Program Gallaudet University WashingtonDC United States The Grainger College of Engineering University of Illinois Urbana-Champaign Urbana-ChampaignIL United States Department of Computational Media University of California Santa Cruz Santa CruzCA United States Department of Hearing and Speech Sciences University of Maryland College Park College ParkMD United States Neuroscience and Cognitive Science University of Maryland College Park College ParkMD United States

ISBN: (纸本)9798400713958

Trained and optimized for typical and fluent speech, speech AI works poorly for people with speech diversities, often interrupting them and misinterpreting their speech. The increasing deployment of speech AI in automated phone menus, AI-conducted job interviews, and everyday devices poses tangible risks to people with speech diversities. To mitigate these risks, this workshop aims to build a multidisciplinary coalition and set the research agenda for fair and accessible speech AI. Bringing together a broad group of academics and practitioners with diverse perspectives, including HCI, AI, and other relevant fields such as disability studies, speech language pathology, and law, this workshop will establish a shared understanding of the technical challenges for fair and accessible speech AI, as well as its ramifications in design, user experience, policy, and society. In addition, the workshop will invite and highlight first-person accounts from people with speech diversities, facilitating direct dialogues and collaboration between speech AI developers and the impacted communities. The key outcomes of this workshop include a summary paper that synthesizes our learnings and outlines the roadmap for improving speech AI for people with speech diversities, as well as a community of scholars, practitioners, activists, and policy makers interested in driving progress in this domain. © 2025 Copyright held by the owner/author(s).

关键词： Speech enhancement

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An Explainable Deep Neural Network Model Based on Multi-Granularity Co-Attention to Improve Prediction of Drug-Target Binding Affinity

SSRN

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SSRN 2024年

作者： Lin, Yanmei Cao, Aiqing Deng, Lei Liao, Mingzhi Zhang, Ru Zhang, Hao Peng, Yuzhong Guangxi Key Lab of Human-machine Interaction and Intelligent Decision Nanning Normal University Nanning530001 China Guangxi Academy of Sciences Nanning530007 China School of Computer Science and Engineering Central South University Changsha410083 China Center of Bioinformatics College of Life Sciences Northwest A&F University Shaanxi Yangling712100 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518000 China Center for Applied Mathematics of Guangxi Nanning Normal University Nanning530100 China

The prediction of drug-target interactions is pivotal in modern new drug development and drug repositioning. Nonetheless, current methods for predicting drug-target interactions often lose essential molecular structure information during the modeling process, leading to low prediction accuracy. This work proposes rMolGIN, a novel graph neural network with residual connectivity for molecular feature learning. rMolGIN not only takes into account the differences in chemical bonding properties and atomic neighborhood interactions, but also captures global and local structural information of drug molecules. Furthermore, we propose a novel drug-target affinity model based on rMolGIN and deep neural networks, coupled with a multi-granularity co-attention mechanism called HMCoDTA to capture comprehensive structural insights from both drugs and proteins. The proposed innovative model allows for comprehensive insight into the structural relationships between drugs and proteins, facilitating a more accurate prediction of binding affinities. To validate the effectiveness of our proposed methods, we conducted extensive experiments on three benchmark datasets of drug-target binding affinity, comparing HMCoDTA against 19 state-of-the-art models. Notably, the results show that HMCoDTA outperforms existing methods, demonstrating the effectiveness and advantages of our model in predicting drug-target binding affinity. © 2024, The Authors. All rights reserved.

关键词： Prediction models

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Eye movement feature classification for soccer expertise identification in virtual reality

arXiv

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arXiv 2020年

作者： Hosp, Benedikt Schultz, Florian Kasneci, Enkelejda Höner, Oliver Perception Engineering Human-Computer-Interaction University of Tuebingen Germany Institute of Sport Science University of Tuebingen Germany

Latest research in expertise assessment of soccer players pronounced the importance of perceptual skills. Former research focused either on high experimental control or natural presentation mode. To assess perceptual skills of athletes, in an optimized manner, we captured omnidirectional in-field scenes, showed to 12 expert, 9 intermediate and 13 novice goalkeepers from soccer on virtual reality glasses. All scenes where shown from the same natural goalkeeper perspective and ended after the return pass to the goalkeeper. Based on their responses and gaze behavior we classified their expertise with common machine learning techniques. This pilot study shows promising results for objective classification of goalkeepers expertise based on their gaze behaviour. Copyright © 2020, The Authors. All rights reserved.

关键词： Sports

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Augmented reality and robotics in education: A systematic literature review

Computers in Human Behavior: Artificial Humans

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computers in human Behavior: Artificial humans 2025年 4卷

作者： Christina Pasalidou Chris Lytridis Avgoustos Tsinakos Nikolaos Fachantidis Laboratory of Informatics & Robotic Applications in Education and Society Department of Educational and Social Policy University of Macedonia Thessaloniki Greece Human-Machines Interaction (HUMAIN) Lab Department of Computer Science Democritus University of Thrace Kavala Greece Advanced Educational Technologies and Mobile Applications (AETMA) Lab Department of Computer Science Democritus University of Thrace Kavala Greece

Integrating cutting-edge technologies into education has been a continuous goal to enhance teaching and learning experiences. Augmented Reality (AR) and robotics are two emerging technologies that have shown promise in transforming educational environments. This paper presents a systematic review of the literature on the combination of AR and robotics for educational purposes, identifying key applications, benefits, and trends. Using the PRISMA methodology, 69 relevant studies from five major databases were analysed and categorised into three themes: (a) AR and Socially Assistive Robots (SAR), (b) AR-assisted educational robotics, and (c) AR in robotics/engineering education. The review provides insights into how different AR-enhanced robotics applications across primary, secondary, and higher education, provide visualizations, multimodal feedback, and immersive experiences. Key findings suggest that while interactive features of AR and the embodiment of robots show promising results for learning, fostering motivation, excitement, positive attitudes, and enriched educational experiences, challenges such as technological complexity and cost remain barriers to widespread adoption. Future research should focus on pedagogical frameworks and large-scale implementations to optimize AR-robotics integration in diverse educational settings.

关键词： Robotics Augmented reality HRI Education

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Stitching Together the Experiences of Disabled Knitters 21

Stitching Together the Experiences of Disabled Knitters

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Proceedings of the 2021 CHI Conference on human Factors in Computing Systems

作者： Taylor Gotfrid Kelly Mack Kathryn J Lum Evelyn Yang Jessica Hodgins Scott E Hudson Jennifer Mankoff University of Washington United States Make4All University of Washington United States Robotics Institute Carnegie Mellon University United States Human-Computer Interaction Institute Carnegie Mellon University United States Allen School of Computer Science and Engineering University of Washington United States

ISBN: (纸本)9781450380966

Knitting is a popular craft that can be used to create customized fabric objects such as household items, clothing and toys. Additionally, many knitters find knitting to be a relaxing and calming exercise. Little is known about how disabled knitters use and benefit from knitting, and what accessibility solutions and challenges they create and encounter. We conducted interviews with 16 experienced, disabled knitters and analyzed 20 threads from six forums that discussed accessible knitting to identify how and why disabled knitters knit, and what accessibility concerns remain. We additionally conducted an iterative design case study developing knitting tools for a knitter who found existing solutions insufficient. Our innovations improved the range of stitches she could produce. We conclude by arguing for the importance of improving tools for both pattern generation and modification as well as adaptations or modifications to existing tools such as looms to make it easier to track progress

关键词： Accessibility craft knitting

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An alternate statistical lens to look at collaboration data: Extreme value theory 13

An alternate statistical lens to look at collaboration data:...

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13th International Conference on computer Supported Collaborative Learning - A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, CSCL 2019

作者： Sharma, Kshitij Olsen, Jennifer Department of Computer Science Norwegian University of Science and Technology Norway Computer Human Interaction Lab in Learning and Instruction École Polytechnique Fédérale de Lausanne Switzerland

ISBN: (纸本)9781732467231

To provide beneficial feedback to students during their collaboration, it is important to identify behaviors that are indicative of good collaboration. However, in a collaborative learning session, students engage in a range of behaviors and it can be difficult to indicate which of those behaviors correlate with higher outcomes. In this paper, we propose using Extreme Value Theory (EVT), a method that considers the data points in the tail (upper or lower) of the distribution, to analyse the relationship between collaborative process variables and outcome measures through insights derived from high impact, low-frequency events. Specifically, in this paper, we analyse the relationship between dual gaze patterns and outcome measures across two different datasets. In both datasets we found that students with lower outcomes had lower focus during the collaborative session. This paper provides a contribution by both introducing EVT as a viable method for analysing CSCL data as well as demonstrating the effectiveness of eyetracking as a collaborative indicator to use to adapt to in real-time. © ISLS.

关键词： Students

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Animo: Sharing biosignals on a smartwatch for lightweight social connection

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Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019年第1期3卷 1–19页

作者： Liu, Fannie Esparza, Mario Pavlovskaia, Maria Kaufman, Geoff Dabbish, Laura Monroy-Hernández, Andrés Human-Computer Interaction Institute School of Computer Science Carnegie Mellon University 5000 Forbes Ave. PittsburghPA15213 United States Snap Inc. SeattleWA98121 United States

We present Animo, a smart watch app that enablespeopleto share and view each other's biosignals. Wedesigned and engineered Animo to explore new ground for smartwatch-based biosignals social computing systems: identifying opportunities where these systems can support lightweight and mood-centric interactions. In our work we develop, explore, and evaluate several innovative features designed for dyadic communication of heart rate. We discuss the results of a two-week study (N=34), including new communication patterns participants engaged in, and outline the design landscape for communicating with biosignals on smartwatches. © 2019 Association for Computing Machinery.

关键词： Heart

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Heart-brain axis:low blood pressure during off-pump CABG surgery is associated with postoperative heart failure

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Military Medical Research 2025年第5期 799-802页

作者： Xiu-Yun Liu Jing-Jing Mu Jian-Ge Han Mei-Jun Pang Kuo Zhang Wen-Qian Zhai Nan Su Guang-Jian Ni Zhi-Gang Guo Dong Ming Academy of Medical Engineering and Translational Medicine Tianjin University State Key Laboratory of Advanced Medical Materials and Devices Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Department of Anesthesiology Tianjin University Chest HospitalTianjin Key Laboratory of Cardiovascular Emergency and Critical CareTianjin Municipal Science and Technology Bureau Department of Cardiac Surgery Tianjin University Chest HospitalTianjin Key Laboratory of Cardiovascular Emergency and Critical CareTianjin Municipal Science and Technology Bureau

Dear Editor,The primary objective of the letter is to emphasize the importance of personalized management of arterial blood pressure (ABP) in the context of off-pump coronary artery bypass grafting (CABG) *** artery disease,a leading global cause of mortality,necessitates a substantial number of cardiac surgeries,with approximately 400,000CABG operations conducted annually in the United *** heart failure (HF) is a common occurrence a?t er CABG surgery,with readmission rates within 30 d due to HF ranging from 12%to 16%.

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