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检索条件"机构=Key Laboratory for Computer Vision and Pattern Recognition"
575 条 记 录,以下是111-120 订阅
Communication via eye blinks and eyebrow raises: Video-based human-computer interfaces
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Universal Access in the Information Society 2003年 第4期2卷 359-373页
作者: Grauman, K. Betke, M. Lombardi, J. Gips, J. Bradski, G.R. Vision Interface Group AI Laboratory Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Computer Science Department Boston University 111 Cummington St BostonMA02215 United States EagleEyes Computer Science Department Boston College Fulton Hall Chestnut HillMA02467 United States Vision Graphics and Pattern Recognition Microcomputer Research Laboratory Intel Corporation SC12-303 2200 Mission College Blvd Santa ClaraCA95054-1537 United States
Two video-based human-computer interaction tools are introduced that can activate a binary switch and issue a selection command. "BlinkLink," as the first tool is called, automatically detects a user's e... 详细信息
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Fast single image dehazing through Edge-Guided Interpolated Filter
Fast single image dehazing through Edge-Guided Interpolated ...
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IAPR International Conference on Machine vision Applications (MVA)
作者: Ximei Zhu Ying Li Yu Qiao Shenzhen Key lab of Computer Vision Pattern Recognition The Chinese University of Hong Kong Hong Kong SAR
Images and videos taken in foggy weather often suffer from low visibility. Recent studies demonstrate the effectiveness of dark channel prior [3] and guided filter [4] based approaches for image dehazing. However, the... 详细信息
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EFFICIENT ONLINE LABEL CONSISTENT HASHING FOR LARGE-SCALE CROSS-MODAL RETRIEVAL
EFFICIENT ONLINE LABEL CONSISTENT HASHING FOR LARGE-SCALE CR...
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2021 IEEE International Conference on Multimedia and Expo, ICME 2021
作者: Yi, Jinhan Liu, Xin Cheung, Yiu-Ming Xu, Xing Fan, Wentao He, Yi Department of Computer Science and Technology Huaqiao University Xiamen361021 China Xiamen Key Lab. of Computer Vision and Pattern Recognition Fujian Key Lab. of Big Data Intelligence and Security China Department of Computer Science Hong Kong Baptist University Kowloon Hong Kong School of Computer Science and Engineering University of Electronic Science and Technology of China China Provincial Key Laboratory for Computer Information Processing Technology Soochow University China
Existing cross-modal hashing still faces three challenges: (1) Most batch-based methods are unsuitable for processing large-scale and streaming data. (2) Current online methods often suffer from insufficient semantic ... 详细信息
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Gene Expression Clustering: a Novel Graph Partitioning Approach
Gene Expression Clustering: a Novel Graph Partitioning Appro...
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International Joint Conference on Neural Networks (IJCNN)
作者: Yanhua Chen Ming Dong Manjeet Rege Machine Vision and Pattern Recognition Laboratory Department of Computer Science Wayne State University Detroit MI USA
In order to help understand how the genes are affected by different disease conditions in a biological system, clustering is typically performed to analyze gene expression data. In this paper, we propose to solve the ... 详细信息
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Evaluation of Unconditioned Deep Generative Synthesis of Retinal Images  20th
Evaluation of Unconditioned Deep Generative Synthesis of Ret...
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20th International Conference on Advanced Concepts for Intelligent vision Systems, ACIVS 2020
作者: Kaplan, Sinan Lensu, Lasse Laaksonen, Lauri Uusitalo, Hannu Computer Vision and Pattern Recognition Laboratory Lappeenranta-Lahti University of Technology LUT P.O. Box 20 Lappeenranta53850 Finland Department of Ophthalmology Faculty of Health and Biotechnology Tampere University and Tays Eye Center Tampere Finland
Retinal images have been increasingly important in clinical diagnostics of several eye and systemic diseases. To help the medical doctors in this work, automatic and semi-automatic diagnosis methods can be used to inc... 详细信息
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Neural Transformation Fields for Arbitrary-Styled Font Generation
Neural Transformation Fields for Arbitrary-Styled Font Gener...
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Conference on computer vision and pattern recognition (CVPR)
作者: Bin Fu Junjun He Jianjun Wang Yu Qiao ShenZhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shanghai Artificial Intelligence Laboratory
Few-shot font generation (FFG), aiming at generating font images with a few samples, is an emerging topic in recent years due to the academic and commercial values. Typically, the FFG approaches follow the style-conte...
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Fast DCT-I, DCT-III, and DCT-IV via Moments
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Eurasip Journal on Applied Signal Processing 2005年 第12期2005卷 1902-1909页
作者: Liu, J.G. Liu, Y.Z. Wang, G.Y. Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China Department of Computer Science and Engineering China University of Geosciences Wuhan 430074 China Key Laboratory of State Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China
This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. Thi... 详细信息
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Abstract: Learning to avoid poor images: towards task-aware c-arm cone-beam ct trajectories
Abstract: Learning to avoid poor images: towards task-aware ...
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International workshop on Algorithmen - Systeme - Anwendungen, 2020
作者: Zaech, Jan-Nico Gao, Cong Bier, Bastian Taylor, Russell Maier, Andreas Navab, Nassir Unberath, Mathias Laboratory for Computational Sensing and Robotics Johns Hopkins University Baltimore United States Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Computer Vision Laboratory Eidgenössische Technische Hochschule Zürich Zürich Germany
Metal artifacts in computed tomography (CT) arise from a mismatch between physics of image formation and idealized assumptions during tomographic reconstruction. These artifacts are particularly strong around metal im... 详细信息
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Classifiability based omnivariate decision trees
Classifiability based omnivariate decision trees
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International Joint Conference on Neural Networks (IJCNN)
作者: Y. Li M. Dong Machine Vision and Pattern Recognition Laboratory Department of Computer Science Wayne State University Detroit MI USA
Decision trees represent a simple and powerful method of induction from labeled examples. Univariate decision trees consider the value of a single attribute at each node, leading to the splits that are parallel to the... 详细信息
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UNIFORMER: UNIFIED TRANSFORMER FOR EFFICIENT SPATIOTEMPORAL REPRESENTATION LEARNING  10
UNIFORMER: UNIFIED TRANSFORMER FOR EFFICIENT SPATIOTEMPORAL ...
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10th International Conference on Learning Representations, ICLR 2022
作者: Li, Kunchang Wang, Yali Gao, Peng Song, Guanglu Liu, Yu Li, Hongsheng Qiao, Yu ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Shanghai AI Laboratory Shanghai China SenseTime Research The Chinese University of Hong Kong Hong Kong
It is a challenging task to learn rich and multi-scale spatiotemporal semantics from high-dimensional videos, due to large local redundancy and complex global dependency between video frames. The recent advances in th... 详细信息
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