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检索条件"机构=Research Center of Machine Learning and Data Analysis"
301 条 记 录,以下是221-230 订阅
排序:
Ndmfcs: An Automatic Fruit Counting System in Modern Apple Orchard Using Abatement of Abnormal Fruit Detection
SSRN
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SSRN 2023年
作者: Wu, Zhenchao Sun, Xiaoming Jiang, Hanhui Mao, Wulan Li, Rui Andriyanov, Nikita Soloviev, Vladimir Fu, Longsheng College of Mechanical and Electronic Engineering Northwest A&F University Shaanxi Yangling712100 China Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs Shaanxi Yangling712100 China Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service Shaanxi Yangling712100 China Northwest A&F University Shenzhen Research Institute Guangdong Shenzhen518000 China Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation Moscow125167 Russia Institute of Agricultural Mechanization Xinjiang Academy of Agricultural Sciences Urumqi830000 China
Automatic fruit counting is an important task for growers to estimate yield and manage orchards. Although many deep-learning-based fruit detection algorithms have been developed to improve performance of automatic fru... 详细信息
来源: 评论
Metadata Concepts for Advancing the Use of Digital Health Technologies in Clinical research
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Digital Biomarkers 2019年 第3期3卷 116-132页
作者: Badawy, Reham Hameed, Farhan Bataille, Lauren Little, Max A. Claes, Kasper Saria, Suchi Cedarbaum, Jesse M. Stephenson, Diane Neville, Jon Maetzler, Walter Espay, Alberto J. Bloem, Bastiaan R. Simuni, Tanya Karlin, Daniel R. School of Computer Science University of Birmingham Birmingham United Kingdom Digital Medicine and Pfizer Innovation Research Lab Early Clinical Development Pfizer Inc. CambridgeMA United States College of Computer and Information Science Northeastern University BostonMA United States Analytics Informatics and Business Intelligence Chief Digital Office Pfizer Inc. New YorkNY United States Michael J. Fox Foundation for Parkinson's Research New YorkNY United States Media Lab Massachusetts Institute of Technology CambridgeMA United States UCB Biopharma Brussels Belgium Machine Learning and Healthcare Laboratory Departments of Computer Science Statistics and Health Policy Malone Center for Engineering in Healthcare Armstrong Institute for Patient Safety and Quality Johns Hopkins University BaltimoreMD United States Biogen CambridgeMA United States Critical Path Institute TucsonAZ United States Clinical Data Interchange Standards Consortium AustinTX United States Department of Neurology Christian Albrecht University Kiel Germany James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders University of Cincinnati CincinnatiOH United States Department of Neurology Donders Institute for Brain Cognition and Behavior Radboud University Medical Center Nijmegen Netherlands Department of Neurology Gardner Center for Parkinson's Disease and Movement Disorders UC Gardner Neuroscience Institute University of Cincinnati CincinnatiOH United States Tufts University School of Medicine BostonMA United States HealthMode New YorkNY United States School of Engineering and Applied Science Aston University BirminghamB47ET United Kingdom
Digital health technologies (smartphones, smartwatches, and other body-worn sensors) can act as novel tools to aid in the diagnosis and remote objective monitoring of an individual's disease symptoms, both in clin... 详细信息
来源: 评论
S3Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching
arXiv
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arXiv 2024年
作者: Wang, Xue Zhou, Tian Zhu, Jianqing Liu, Jialin Yuan, Kun Yao, Tao Yin, Wotao Jin, Rong Cai, Han Qin Alibaba Group BellevueWA98004 United States Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Department of Statistics and Data Science University of Central Florida OrlandoFL32816 United States Center for Machine Learning Research Peking University Beijing100871 China Antai College of Economics and Management Shanghai Jiao Tong University Shanghai200030 China Meta Menlo ParkCA94025 United States Department of Statistics and Data Science Department of Computer Science University of Central Florida OrlandoFL32816 United States
Attention based models have achieved many remarkable breakthroughs in numerous applications. However, the quadratic complexity of Attention makes the vanilla Attention based models hard to apply to long sequence tasks... 详细信息
来源: 评论
Sports-QA: A Large-Scale Video Question Answering Benchmark for Complex and Professional Sports
arXiv
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arXiv 2024年
作者: Li, Haopeng Deng, Andong Liu, Jun Rahmani, Hossein Guo, Yulan Schiele, Bernt Bennamoun, Mohammed Ke, Qiuhong School of Computing and Information Systems University of Melbourne Australia Center for Research in Computer Vision University of Central Florida United States Pillar Singapore University of Technology and Design Singapore School of Computing and Communications Lancaster University United Kingdom School of Electronics and Communication Engineering Sun Yat-sen University China Department of Computer Vision and Machine Learning Max Planck Institute for Informatics Saarland Informatics Campus Germany School of Physics Maths and Computing University of Western Australia Australia Department of Data Science & AI Monash University Australia
Reasoning over sports videos for question answering is an important task with numerous applications, such as player training and information retrieval. However, this task has not been explored due to the lack of relev... 详细信息
来源: 评论
Florid – a Nationwide Identification Service for Plants from Photos and Habitat Information
SSRN
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SSRN 2024年
作者: Brun, Philipp de Witte, Lucienne Popp, Manuel Richard Zurell, Damaris Karger, Dirk Nikolaus Descombes, Patrice de Lutio, Riccardo Wegner, Jan Dirk Bornand, Christophe Eggenberg, Stefan Olevski, Tasko Zimmermann, Niklaus E. Swiss Federal Research Institute WSL Birmensdorf8903 Switzerland Musée et jardins botaniques cantonaux Lausanne1007 Switzerland Institute of Biochemistry and Biology University of Potsdam Potsdam14469 Germany EcoVision Lab Photogrammetry and Remote Sensing ETH Zurich Zürich8092 Switzerland Department of Mathematical Modeling and Machine Learning University of Zurich Zürich8057 Switzerland InfoFlora Switzerland Bern3013 Switzerland Swiss Data Science Center ETH Zurich Zürich8092 Switzerland University of Basel Switzerland
Citizen science has become key to biodiversity monitoring but critically depends on accurate quality control that is scalable and tailored to the focal region. We developed FlorID, a free-to-use identification service... 详细信息
来源: 评论
Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy
arXiv
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arXiv 2024年
作者: Handa, Palak Mahbod, Amirreza Schwarzhans, Florian Woitek, Ramona Goel, Nidhi Dhir, Manas Chhabra, Deepti Jha, Shreshtha Sharma, Pallavi Thakur, Vijay Chawla, Simarpreet Singh Gunjan, Deepak Kakarla, Jagadeesh Raman, Balasubramanian Research Center for Medical Image Analysis and Artificial Intelligence Department of Medicine Danube Private University Krems Austria Department of Electronics and Communication Engineering Indira Gandhi Delhi Technical University for Women Delhi India Department of Artificial Intelligence and Data Sciences Indira Gandhi Delhi Technical University for Women Delhi India Department of Artificial Intelligence and Machine Learning University School of Automation and Robotics Guru Gobind Singh Indraprastha University Delhi India Department of Electronics and Communication Engineering Delhi Technological University Delhi India Columbia University New YorkNY United States Department of Gastroenterology and HNU All India Institute of Medical Sciences Delhi India Chennai Kancheepuram India Department of Computer Science and Engineering Indian Institute of Technology Roorkee India
We present the Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy. It was virtually organized by the research center for Medical Image analysis and Artificial Intelligenc... 详细信息
来源: 评论
Unlocking the Potential of Digital Pathology: Novel Baselines for Compression
arXiv
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arXiv 2024年
作者: Fischer, Maximilian Neher, Peter Schuffler, Peter Ziegler, Sebastian Xiao, Shuhan Peretzke, Robin Clunie, David Ulrich, Constantin Baumgartner, Michael Muckenhuber, Alexander Almeida, Silvia Dias Gotz, Michael Kleesiek, Jens Nolden, Marco Braren, Rickmer Maier-Hein, Klaus Heidelberg Germany Partner site Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Medical Faculty Heidelberg University Heidelberg Germany Clinic of Diagnostics and Interventional Radiology Section Experimental Radiology Ulm University Medical Centre Ulm Germany Institute of Pathology TUM School of Medicine and Health Technical University of Munich Munich Germany Department of Diagnostic and Interventional Radiology Faculty of Medicine Technical University of Munich Munich Germany University Medicine Essen Essen Germany Partner site Essen Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Research Campus M2OLIE Mannheim Germany PixelMed Publishing BangorPA United States Munich Center for Machine Learning Munich Germany Helmholtz Imaging German Cancer Research Center Germany
Digital pathology offers a groundbreaking opportunity to transform clinical practice in histopathological image analysis, yet faces a significant hurdle: the substantial file sizes of pathological Whole Slide Images (... 详细信息
来源: 评论
Astrocytes mediate analogous memory in a multi-layer neuron-astrocytic network
arXiv
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arXiv 2021年
作者: Tsybina, Yuliya Kastalskiy, Innokentiy Krivonosov, Mikhail Zaikin, Alexey Kazantsev, Victor Gorban, Alexander Gordleeva, Susanna Scientific and Educational Mathematical Center 'Mathematics of Future Technology' Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia Laboratory of Autowave Processes Institute of Applied Physics Russian Academy of Sciences Nizhny Novgorod Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia Neuroscience Research Institute Samara State Medical University Samara Russia Dept of Mathematics Leicester University Leicester United Kingdom Centre for Analysis of Complex Systems Sechenov First Moscow State Medical University Sechenov University Moscow Russia Institute for Women's Health and Department of Mathematics University College London London United Kingdom
Modeling the neuronal processes underlying short-term working memory remains the focus of many theoretical studies in neuroscience. Here we propose a mathematical model of spiking neuron network (SNN) demonstrating ho... 详细信息
来源: 评论
Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures
arXiv
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arXiv 2024年
作者: Kirchhoff, Yannick Rokuss, Maximilian R. Roy, Saikat Kovacs, Balint Ulrich, Constantin Wald, Tassilo Zenk, Maximilian Vollmuth, Philipp Kleesiek, Jens Isensee, Fabian Maier-Hein, Klaus Heidelberg Division of Medical Image Computing Germany Faculty of Mathematics and Computer Science Heidelberg University Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Heidelberg Karlsruhe Germany Medical Faculty Heidelberg Heidelberg University Heidelberg Germany Helmholtz Imaging German Cancer Research Center Heidelberg Germany Clinic for Neuroradiology University Hospital Bonn Bonn Germany Medical Faculty Bonn University of Bonn Bonn Germany University Hospital Essen Essen Germany West German Cancer Center Essen University Hospital Essen Essen Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany
Accurately segmenting thin tubular structures, such as vessels, nerves, roads or concrete cracks, is a crucial task in computer vision. Standard deep learning-based segmentation loss functions, such as Dice or Cross-E... 详细信息
来源: 评论
A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer
arXiv
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arXiv 2024年
作者: Machado, Inês P. Reithmeir, Anna Kogl, Fryderyk Rundo, Leonardo Funingana, Gabriel Reinius, Marika Mungmeeprued, Gift Gao, Zeyu McCague, Cathal Kerfoot, Eric Woitek, Ramona Sala, Evis Ou, Yangming Brenton, James Schnabel, Julia Crispin, Mireia Department of Oncology University of Cambridge United Kingdom Cancer Research UK Cambridge Institute University of Cambridge United Kingdom Early Cancer Institute University of Cambridge United Kingdom School of Computation Information & Technology Technical University of Munich Germany Institute of Machine Learning in Biomedical Imaging Helmholtz Munich Germany Department of Information and Electrical Engineering University of Salerno Italy School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Research Center for Medical Image Analysis and AI Danube University Austria Department of Radiologic Sciences Università Cattolica del Sacro Cuore Italy Department of Radiology Boston Children’s Hospital Harvard Medical School United States
High-grade serous ovarian carcinoma (HGSOC) is characterised by significant spatial and temporal heterogeneity, typically manifesting at an advanced metastatic stage. A major challenge in treating advanced HGSOC is ef... 详细信息
来源: 评论