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检索条件"机构=Pattern Recognition and Intelligent System"
326 条 记 录,以下是41-50 订阅
排序:
Zero-Shot Audio Captioning Using Soft and Hard Prompts
IEEE Transactions on Audio, Speech and Language Processing
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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 2045-2058页
作者: Yiming Zhang Xuenan Xu Ruoyi Du Haohe Liu Yuan Dong Zheng-Hua Tan Wenwu Wang Zhanyu Ma Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Centre for Vision Speech and Signal Processing University of Surrey Guildford U.K. Department of Electronic Systems Aalborg University Aalborg Denmark
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 set from the same dataset. Su... 详细信息
来源: 评论
Fire Detection Based on Flame Enhancement for Weak Fires  19th
Fire Detection Based on Flame Enhancement for Weak Fires
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19th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2024
作者: Chen, Kuan Wen, Wen Feng, Fujian Xu, Xiang Liang, Yihui School of Computer Guangdong University of Technology Guangzhou510000 China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan528400 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang550025 China
Detecting weak fire, such as overexposed and highly transparent flames, remains a significant challenge in vision-based fire detection. Convolutional Neural Network (CNN) based methods are widely used for automatic fi... 详细信息
来源: 评论
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face recognition
arXiv
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arXiv 2022年
作者: Zhong, Yaoyao Deng, Weihong Hu, Jiani Zhao, Dongyue Li, Xian Wen, Dongchao The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Co. Ltd China
Deep face recognition has achieved great success due to large-scale training databases and rapidly developing loss functions. The existing algorithms devote to realizing an ideal idea: minimizing the intra-class dista... 详细信息
来源: 评论
Adaptive Pixel Pair Generation Strategy for Image Matting Methods Based on Pixel Pair Optimization  19th
Adaptive Pixel Pair Generation Strategy for Image Matting Me...
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19th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2024
作者: Zheng, Jiamin Wen, Wen Liang, Yihui Feng, Fujian Xu, Xiang School of Computer Guangdong University of Technology Guangzhou510000 China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan528400 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang550025 China
Natural image matting plays a crucial role in numerous real-world applications. Image matting methods based on pixel pair optimization is a type of matting algorithm, which has significant advantages in parallel compu... 详细信息
来源: 评论
Oracle Character recognition using Unsupervised Discriminative Consistency Network
arXiv
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arXiv 2023年
作者: Wang, Mei Deng, Weihong Su, Sen The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China
Ancient history relies on the study of ancient characters. However, real-world scanned oracle characters are difficult to collect and annotate, posing a major obstacle for oracle character recognition (OrCR). Besides,... 详细信息
来源: 评论
Mixture Loss Function-based Classification Network for Few-shot Learning
Mixture Loss Function-based Classification Network for Few-s...
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Computing, Robotics and system Sciences (ICRSS), International Conference on
作者: Yansha Zhang Feng Pan Jie Wang Lin Wang College of Date Science and Information Engineering GuiZhou Minzu University Guiyang China Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province Guiyang China
Data augmentation technology can effectively solve the problem of few-shot image classification, but many approaches based on data augmentation generated sample have poor discriminability, which negatively affects the... 详细信息
来源: 评论
Learning Invariant Visual Representations for Compositional Zero-Shot Learning
arXiv
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arXiv 2022年
作者: Zhang, Tian Liang, Kongming Du, Ruoyi Sun, Xian Ma, Zhanyu Guo, Jun Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications China Aerospace Information Research Institute Chinese Academy of Sciences China
Compositional Zero-Shot Learning (CZSL) aims to recognize novel compositions using knowledge learned from seen attribute-object compositions in the training set. Previous works mainly project an image and a compositio... 详细信息
来源: 评论
MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery
arXiv
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arXiv 2025年
作者: Li, Yansheng Wu, Yuning Cheng, Gong Tao, Chao Dang, Bo Wang, Yu Zhang, Jiahao Zhang, Chuge Liu, Yiting Tang, Xu Ma, Jiayi Zhang, Yongjun Information and computing science from Shandong University Weihai China Pattern recognition and intelligent system from the Huazhong University of Science and Technology Wuhan China Computer science and technology from Wuhan University Wuhan China Xidian University Xi’an China Pattern recognition and intelligent systems from Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong China University of Science and Technology Remote sensing science and technology from Wuhan University Wuhan China School of Remote Sensing and Information Engineering Wuhan University Wuhan China Electronic circuit and system from Xidian University Xi’an China University of Colorado at Boulder BoulderCO United States Control science and engineering from the Huazhong University of Science and Technology Wuhan China Geodesy and photography from Wuhan University Wuhan China
Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manually zooming remote sensing images at di... 详细信息
来源: 评论
Natural image matting based on image inpainting
Natural image matting based on image inpainting
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Computer Graphics, Image and Virtualization (ICCGIV), International Conference on
作者: Yuan Zhang Mian Tan Zhulian Zhou Yuan Yang Yihui Liang Fujian Feng Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Computer Science University of Electronic Science and Technology China Zhongshan China
Deep image matting is a hot problem with applications in computer vision and image processing. It has been widely used in image composition, film production and video editing etc. The current matting method based on i... 详细信息
来源: 评论
GeoPix: Multi-Modal Large Language Model for Pixel-level Image Understanding in Remote Sensing
arXiv
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arXiv 2025年
作者: Ou, Ruizhe Hu, Yuan Zhang, Fan Chen, Jiaxin Liu, Yu Pattern Recognition and Intelligent System Lab School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Institute of Remote Sensing and Geographic Information Systems School of Earth and Space Sciences Peking University Beijing100871 China Peking University Ordos Research Institute of Energy Ordos017000 China
Multi-modal large language models (MLLMs) have achieved remarkable success in image- and region-level remote sensing (RS) image understanding tasks, such as image captioning, visual question answering, and visual grou... 详细信息
来源: 评论