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检索条件"机构=Department of Computer Vision and Pattern Recognition"
288 条 记 录,以下是81-90 订阅
排序:
FDDH: Fast discriminative discrete hashing for large-scale cross-modal retrieval
arXiv
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arXiv 2021年
作者: Liu, Xin Wang, Xingzhi Cheung, Yiu-Ming Department of Computer Science Huaqiao University Xiamen Key Laboratory of Computer Vision and Pattern Recognition Fujian Key Laboratory of Big Data Intelligence and Security Xiamen361021 China School of Electronics and Information Technology Sun Yat-sen University Guangzhou510006 China Department of Computer Science Hong Kong Baptist University Hong Kong Hong Kong
Cross-modal hashing, favored for its effectiveness and efficiency, has received wide attention to facilitating efficient retrieval across different modalities. Nevertheless, most existing methods do not sufficiently e... 详细信息
来源: 评论
EDEN: Deep feature distribution pooling for Saimaa ringed seals pattern matching
arXiv
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arXiv 2021年
作者: Chelak, Ilia Nepovinnykh, Ekaterina Eerola, Tuomas Kälviäinen, Heikki Belykh, Igor Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Lappeenranta-Lahti University of Technology LUT School of Engineering Science Department of Computational Engineering Computer Vision and Pattern Recognition Laboratory P.O.Box 20 Lappeenranta53850 Finland
In this paper, pelage pattern matching is considered to solve the individual re-identification of the Saimaa ringed seals. Animal re-identification together with the access to large amount of image material through ca... 详细信息
来源: 评论
A Survey of the Self Supervised Learning Mechanisms for vision Transformers
arXiv
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arXiv 2024年
作者: Khan, Asifullah Sohail, Anabia Fiaz, Mustansar Hassan, Mehdi Afridi, Tariq Habib Marwat, Sibghat Ullah Munir, Farzeen Ali, Safdar Naseem, Hannan Zaheer, Muhammad Zaigham Ali, Kamran Sultana, Tangina Tanoli, Ziaurrehman Akhter, Naeem Pattern Recognition Lab DCIS PIEAS Nilore Islamabad45650 Pakistan PIEAS Nilore Islamabad45650 Pakistan Deep Learning Lab Center for Mathematical Sciences PIEAS Nilore Islamabad45650 Pakistan Center of Secure Cyber-Physical Security Systems Khalifa University Abu Dhabi United Arab Emirates IBM Research United States Department of Computer Science Air University Islamabad Pakistan Department of Computer Science and Engineering Kyung Hee University Global Campus 1732 Gyeonggi-do Yongin17104 Korea Republic of Department of Electrical Engineering and Automation Aalto University Finland Finnish Center of Artificial Center Finland Faculty of Engineering and Green Technology Universiti Tunku Abdul Rahman Malaysia Computer Vision Department Mohamed Bin Zayed University of Artificial Intelligence United Arab Emirates Karachi Pakistan Department of Electronics and Communication Engineering Hajee Mohammad Danesh Science and Technology University Bangladesh HiLIFE University of Helsinki Finland
vision Transformers (ViTs) have recently demonstrated remarkable performance in computer vision tasks. However, their parameter-intensive nature and reliance on large amounts of data for effective performance have shi... 详细信息
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68 landmarks are efficient for 3D face alignment: What about more? 3D face alignment method applied to face recognition
TechRxiv
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TechRxiv 2021年
作者: Jabberi, Marwa Wali, Ali Chaudhuri, Bidyut Baran Alimi, Adel M. University of Sousse ISITCom Sousse4011 Tunisia BP 1173 Sfax3038 Tunisia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg South Africa
This paper proposes a 3D face alignment of 2D face images in the wild with noisy landmarks where the objective is to recognize individuals from their single profile image. We first proceed by extracting more than 68 l... 详细信息
来源: 评论
Towards accurate scene text recognition with semantic reasoning networks
arXiv
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arXiv 2020年
作者: Yu, Deli Li, Xuan Zhang, Chengquan Liu, Tao Han, Junyu Liu, Jingtuo Ding, Errui School of Artificial Intelligence University of Chinese Academy of Sciences Department of Computer Vision Technology Baidu Inc National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences
Scene text image contains two levels of contents: visual texture and semantic information. Although the previous scene text recognition methods have made great progress over the past few years, the research on mining ... 详细信息
来源: 评论
AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks
arXiv
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arXiv 2021年
作者: Roy, Swalpa Kumar Paoletti, Mercedes E. Haut, Juan M. Dubey, Shiv Ram Kar, Purbayan Plaza, Antonio Chaudhuri, Bidyut B. The Computer Science and Engineering Alipurduar Government Engineering and Management College 736206 India The Hyperspectral Computing Laboratory Department of Technology of Computers and Communications University of Extremadura Cáceres10003 Spain The Computer Vision and Biometrics Lab Indian Institute of Information Technology Prayagraj Uttar Pradesh Allahabad211015 India The Media Analysis Group Sony Research India Private Limited Karnataka Bangalore560103 India The Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India
Convolutional neural networks (CNNs) are trained using stochastic gradient descent (SGD)-based optimizers. Recently, the adaptive moment estimation (Adam) optimizer has become very popular due to its adaptive momentum... 详细信息
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Towards Accurate Scene Text recognition With Semantic Reasoning Networks
Towards Accurate Scene Text Recognition With Semantic Reason...
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Conference on computer vision and pattern recognition (CVPR)
作者: Deli Yu Xuan Li Chengquan Zhang Tao Liu Junyu Han Jingtuo Liu Errui Ding School of Artificial Intelligence University of Chinese Academy of Sciences National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Department of Computer Vision Technology(VIS) Baidu Inc.
Scene text image contains two levels of contents: visual texture and semantic information. Although the previous scene text recognition methods have made great progress over the past few years, the research on mining ... 详细信息
来源: 评论
Split-Net: Dual Transformer Encoder with Splitting Scene Text Image for Script Identification
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pattern recognition Letters 2025年
作者: Ayush Roy Shivakumara Palaiahnakote Umapada Pal Cheng-Lin Liu PhD Department of Computer Science and Engineering State University of New York Buffalo USA School of Science Engineering and Environment University of Salford Manchester UK Computer Vision and Pattern Recognition Indian Statistical Institute Kolkata India State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation of the Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China
Script identification is vital for understanding scenes and video images. It is challenging due to high variations in physical appearance, typeface design, complex background, distortion, and significant overlap in th...
来源: 评论
Face recognition - A one-shot learning perspective  15
Face recognition - A one-shot learning perspective
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15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
作者: Chanda, Sukalpa Gv, Asish Chakrapani Brun, Anders Hast, Anders Pal, Umapada Doermann, David Department of Information Technology Østfold University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Centre for Image Analysis Uppsala University Sweden Computer Science and Engineering University at Buffalo United States
Ability to learn from a single instance is something unique to the human species and One-shot learning algorithms try to mimic this special capability. On the other hand, despite the fantastic performance of Deep Lear... 详细信息
来源: 评论
MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
arXiv
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arXiv 2021年
作者: Srivastava, Abhishek Jha, Debesh Chanda, Sukalpa Pal, Umapada Johansen, Håvard D. Johansen, Dag Riegler, Michael A. Ali, Sharib Halvorsen, Pål Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India SimulaMet Oslo Norway UiT The Arctic University of Norway Tromsø Norway Østfold University College Halden Norway Indian Statistical Institute Kolkata India The Department of Engineering Science University of Oxford Oxford NIHR Biomedical Research Centre Oxford United Kingdom Oslo Metropolitan University Oslo Norway
Methods based on convolutional neural networks have improved the performance of biomedical image segmentation However, most of these methods cannot efficiently segment objects of variable sizes and train on small and ... 详细信息
来源: 评论