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检索条件"任意字段=2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022"
3917 条 记 录,以下是3661-3670 订阅
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Deep coupling of random ferns  32
Deep coupling of random ferns
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32nd ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2019
作者: Kim, Sangwon Jeong, Mira Lee, Deokwoo Ko, Byoung Chul Dept. of Computer Engineering Keimyung University Daegu42601 Korea Republic of
The purpose of this study is to design a new lightweight explainable deep model instead of deep neural networks (DNN) because of its high memory and processing resource requirement as well as black-box training althou... 详细信息
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Classification of computer generated and natural images based on efficient deep convolutional recurrent attention model  32
Classification of computer generated and natural images base...
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32nd ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2019
作者: Tariang, Diangarti Bhalang Sengupta, Prithviraj Roy, Aniket Chakraborty, Rajat Subhra Naskar, Ruchira Indian Institute of Technology Kharagpur University of Illinois at Chicago Indian Statistical Institute Kolkata India National Instititute of Technology Rourkela India
Most state-of-the-art techniques of distinguishing natural images and computer generated images based on handcrafted feature and Convolutional Neural Network require processing of the entire input image pixels uniform... 详细信息
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Maximally compact and separated features with regular polytope networks  32
Maximally compact and separated features with regular polyto...
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32nd ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2019
作者: Pernici, Federico Bruni, Matteo Baecchi, Claudio Del Bimbo, Alberto MICC – Media Integration and Communication Center University of Florence Italy
Convolutional Neural Networks (CNNs) trained with the Softmax loss are widely used classification models for several vision tasks. Typically, a learnable transformation (i.e. the classifier) is placed at the end of su... 详细信息
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Bidirectional deep residual learning for haze removal  32
Bidirectional deep residual learning for haze removal
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32nd ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2019
作者: Kim, Guisik Park, Jinhee Ha, Suhyeon Kwon, Junseok School of Computer Science and Engineering Chung-Ang University Seoul Korea Republic of
Recently, low-level vision problems has been addressed using residual learning that can learn a discrepancy between hazy and haze-free images. Following this approach, in this paper, we present a new dehazing method b... 详细信息
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Photoplethysmography based stratification of blood pressure using multi information fusion artificial neural network
Photoplethysmography based stratification of blood pressure ...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Dingliang Wang Xuezhi Yang Xuenan Liu Shuai Fang Likun Ma Longwei Li School of Computer and Information Hefei University of Technology Hefei China School of Software Hefei University of Technology Hefei China The First Affiliated Hospital University of Science and Technology of China Hefei China
Regular monitoring of blood pressure (BP) is an effective way to prevent cardiovascular diseases, especially for elderly people. At present, BP measurement mainly relies on cuff-based devices which are inconvenient fo... 详细信息
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Multi-task mutual learning for vehicle re-identification  32
Multi-task mutual learning for vehicle re-identification
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32nd ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2019
作者: Rajamanoharan, Georgia Kanacı, Aytaç Li, Minxian Gong, Shaogang Vision Semantics Ltd Queen Mary University of London
Vehicle re-identification (Re-ID) aims to search a specific vehicle instance across non-overlapping camera views. The main challenge of vehicle Re-ID is that the visual appearance of vehicles may drastically changes a... 详细信息
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Improving socially-aware multi-channel human emotion prediction for robot navigation  32
Improving socially-aware multi-channel human emotion predict...
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32nd ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2019
作者: Bera, Aniket Randhavane, Tanmay Manocha, Dinesh Department of Computer Science University of North Carolina Chapel Hill United States Department of Computer Science University of Maryland College Park United States
We present a real-time algorithm for emotion-aware navigation of a robot among pedestrians. Our approach estimates time-varying emotional behaviors of pedestrians from their faces and trajectories using a combination ... 详细信息
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Mesh Variational Autoencoders with Edge Contraction Pooling
Mesh Variational Autoencoders with Edge Contraction Pooling
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Yu-Jie Yuan Yu-Kun Lai Jie Yang Qi Duan Hongbo Fu Lin Gao Institute of Computing Technology CAS Beijing Key Laboratory of Mobile Computing and Pervasive Device School of Computer Science and Informatics Cardiff University UK SenseTime Research City University of Hong Kong Shenzhen Research Institute of Big Data Shenzhen
3D shape analysis is an important research topic in computer vision and graphics. While existing methods have generalized image-based deep learning to meshes using graph-based convolutions, the lack of an effective po... 详细信息
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Analyzing U-Net Robustness for Single Cell Nucleus Segmentation from Phase Contrast Images
Analyzing U-Net Robustness for Single Cell Nucleus Segmentat...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Chenyi Ling Michael Halter Anne Plant Michael Majurski Jeffrey Stinson Joe Chalfoun Software and Systems Division Information Technology Lab NIST Gaithersburg MD Biosystems and Biomaterials Division Material Measurement Lab NIST Gaithersburg MD
We quantify the robustness of the semantic segmentation model U-Net, applied to single cell nuclei detection, with respect to the following factors: (1) automated vs manual training annotations, (2) quantity of traini... 详细信息
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Fast Hardware-Aware Neural Architecture Search
Fast Hardware-Aware Neural Architecture Search
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Li Lyna Zhang Yuqing Yang Yuhang Jiang Wenwu Zhu Yunxin Liu Microsoft Research Tsinghua University
Designing accurate and efficient convolutional neural architectures for vast amount of hardware is challenging because hardware designs are complex and diverse. This paper addresses the hardware diversity challenge in... 详细信息
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