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检索条件"机构=Pattern Recognition and Intelligent System"
326 条 记 录,以下是71-80 订阅
排序:
Cross-layer navigation convolutional neural network for fine-grained visual classification
arXiv
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arXiv 2021年
作者: Guo, Chenyu Xie, Jiyang Liang, Kongming Sun, Xian Ma, Zhanyu Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China
Fine-grained visual classification (FGVC) aims to classify sub-classes of objects in the same super-class (e.g., species of birds, models of cars). For the FGVC tasks, the essential solution is to find discriminative ... 详细信息
来源: 评论
Zero-Shot Audio Captioning Using Soft and Hard Prompts
arXiv
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arXiv 2024年
作者: Zhang, Yiming Xu, Xuenan Du, Ruoyi Liu, Haohe Dong, Yuan Tan, Zheng-Hua Wang, Wenwu Ma, Zhanyu The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Electronic Systems Aalborg University Aalborg9220 Denmark The Centre for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom
In traditional audio captioning methods, a model is usually trained in a fully supervised manner using a human-annotated dataset containing audio-text pairs and then evaluated on the test sets from the same dataset. S... 详细信息
来源: 评论
Finger in Camera Speaks Everything: Unconstrained Air-Writing for Real-World
arXiv
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arXiv 2024年
作者: Wu, Meiqi Huang, Kaiqi Cai, Yuanqiang Hu, Shiyu Zhao, Yuzhong Wang, Weiqiang School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China Beijing University of Posts and Telecommunications Beijing100876 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Center for Research on Intelligent System and Engineering Institute of Automation Chinese Academy of Sciences Beijing100190 China Center for Research on Intelligent System and Engineering National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China
Air-writing is a challenging task that combines the fields of computer vision and natural language processing, offering an intuitive and natural approach for human-computer interaction. However, current air-writing so... 详细信息
来源: 评论
Structured DropConnect for uncertainty inference in image classification
arXiv
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arXiv 2021年
作者: Zheng, Wenqing Xie, Jiyang Liu, Weidong Ma, Zhanyu Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications Beijing China China Mobile Research Institute Beijing China Beijing Academy of Artificial Intelligence
With the complexity of the network structure, uncertainty inference has become an important task to improve classification accuracy for artificial intelligence systems. For image classification tasks, we propose a str... 详细信息
来源: 评论
Clue me in: Semi-supervised FGVC with out-of-distribution data
arXiv
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arXiv 2021年
作者: Du, Ruoyi Chang, Dongliang Ma, Zhanyu Song, Yi-Zhe Guo, Jun The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China SketchX CVSSP University of Surrey London United Kingdom
Despite great strides made on fine-grained visual classification (FGVC), current methods are still heavily reliant on fully-supervised paradigms where ample expert labels are called for. Semi-supervised learning (SSL)... 详细信息
来源: 评论
TLRM: Task-level Relation Module for GNN-based Few-Shot Learning
TLRM: Task-level Relation Module for GNN-based Few-Shot Lear...
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IEEE Visual Communications and Image Processing (VCIP)
作者: Yurong Guo Zhanyu Ma Xiaoxu Li Yuan Dong Pattern Recognition and Intelligent System Lab. Beijing University of Posts and Telecommunications Beijing China Beijing Academy of Artificial Intelligence Beijing China Lanzhou University of Technology Lanzhou China
Recently, graph neural networks (GNNs) have shown powerful ability to handle few-shot classification problem, which aims at classifying unseen samples when trained with limited labeled samples per class. GNN-based few... 详细信息
来源: 评论
Fgsd: A dataset for fine-grained ship detection in high resolution satellite images
arXiv
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arXiv 2020年
作者: Chen, Kaiyan Wu, Ming Liu, Jiaming Zhang, Chuang Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications Beijing China
Ship detection using high-resolution remote sensing images is an important task, which contribute to sea surface regulation. The complex background and special visual angle make ship detection relies in high quality d... 详细信息
来源: 评论
C-DLinkNet: Considering Multi-level semantic features for human parsing
arXiv
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arXiv 2020年
作者: Lu, Yu Feng, Muyan Wu, Ming Zhang, Chuang Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications Beijing China
Human parsing is an essential branch of semantic segmentation, which is a fine-grained semantic segmentation task to identify the constituent parts of human. The challenge of human parsing is to extract effective sema... 详细信息
来源: 评论
IU-Module: Intersection and Union Module for Fine-Grained Visual Classification
IU-Module: Intersection and Union Module for Fine-Grained Vi...
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IEEE International Conference on Multimedia and Expo (ICME)
作者: Yixiao Zheng Dongliang Chang Jiyang Xie Zhanyu Ma Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications
A predominant viewpoint in previous works of fine-grained visual classification (FGVC) is to the localize discriminative parts by auxiliary networks and extract the part-based finegrained features for classification. ... 详细信息
来源: 评论
Survey on Deep Face Restoration: From Non-blind to Blind and Beyond
arXiv
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arXiv 2023年
作者: Li, Wenjie Wang, Mei Zhang, Kai Li, Juncheng Li, Xiaoming Zhang, Yuhang Gao, Guangwei Deng, Weihong Lin, Chia-Wen The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China The Computer Vision Lab ETH Zürich Zürich Switzerland The School of Communication and Information Engineering Shanghai University Shanghai China The Nanyang Technological University Singapore The Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China The Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan
Face restoration (FR) is a specialized field within image restoration that aims to recover low-quality (LQ) face images into high-quality (HQ) face images. Recent advances in deep learning technology have led to signi... 详细信息
来源: 评论