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检索条件"机构=Pattern Recognition and Intelligence System"
102 条 记 录,以下是1-10 订阅
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Structural Connectivity Enhanced Anisotropic 3D Network for Brain Midline Delineation
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Journal of Beijing Institute of Technology 2023年 第5期32卷 562-578页
作者: Yufan Liu Kongming Liang Yinuo Jing Shen Wang Zhanyu Ma Yiming Li Yizhou Yu Yizhou Wang Jun Guo Pattern Recognition and Intelligent System Laboratory School of Artificial IntelligenceBeijing University of Posts and TelecommunicationsBeijing 100876China. Center on Frontiers of Computing Studies School of Computer SciencePeking UniversityBeijing 100871China AI Lab Deepwise HealthcareBeijing 100089China
Brain midline delineation can facilitate the clinical evaluation of brain midline shift,which has a pivotal role in the diagnosis and prognosis of various brain ***,there are still challenges for brain midline delinea... 详细信息
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Self-Enhanced Training Framework for Referring Expression Grounding
Self-Enhanced Training Framework for Referring Expression Gr...
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IEEE International Conference on Image Processing
作者: Yitao Chen Ruoyi Du Kongming Liang Zhanyu Ma Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing
Weakly-supervised referring expression grounding (REG) aims at locating the image region described by a query sentence, where the mapping between the referential region and query is not available during the training s...
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Adaptive Face recognition Using Adversarial Information Network
arXiv
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arXiv 2023年
作者: Wang, Mei Deng, Weihong Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China
In many real-world applications, face recognition models often degenerate when training data (referred to as source domain) are different from testing data (referred to as target domain). To alleviate this mismatch ca... 详细信息
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KNOWLEDGE TRANSFER BASED FINE-GRAINED VISUAL CLASSIFICATION
KNOWLEDGE TRANSFER BASED FINE-GRAINED VISUAL CLASSIFICATION
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2021 IEEE International Conference on Multimedia and Expo, ICME 2021
作者: Zhang, Siqing Du, Ruoyi Chang, Dongliang Ma, Zhanyu Guo, Jun The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China
Fine-grained visual classification (FGVC) aims to distinguish the sub-classes of the same category and its essential solution is to mine the subtle and discriminative regions. Convolution neural networks (CNNs), which... 详细信息
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Detailed Object Description with Controllable Dimensions
arXiv
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arXiv 2024年
作者: Wang, Xinran Zhang, Haiwen Li, Baoteng Liang, Kongming Sun, Hao He, Zhongjiang Ma, Zhanyu Guo, Jun Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China China Telecom Artificial Intelligence Technology Co. Ltd Beijing100034 China
Object description plays an important role for visually impaired individuals to understand and compare the differences between objects. Recent multimodal large language models (MLLMs) exhibit powerful perceptual abili... 详细信息
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Multi-View Active Fine-Grained recognition
arXiv
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arXiv 2022年
作者: Du, Ruoyi Yu, Wenqing Wang, Heqing Chang, Dongliang Lin, Ting-En Li, Yongbin Ma, Zhanyu Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China
As fine-grained visual classification (FGVC) being developed for decades, great works related have exposed a key direction - finding discriminative local regions and revealing subtle differences. However, unlike ident... 详细信息
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Boosting Facial Expression recognition by A Semi-Supervised Progressive Teacher
arXiv
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arXiv 2022年
作者: Jiang, Jing Deng, Weihong The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China
In this paper, we aim to improve the performance of in-the-wild Facial Expression recognition (FER) by exploiting semi-supervised learning. Large-scale labeled data and deep learning methods have greatly improved the ... 详细信息
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Cycle Label-Consistent Networks for Unsupervised Domain Adaptation
arXiv
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arXiv 2022年
作者: Wang, Mei Deng, Weihong The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China
Domain adaptation aims to leverage a labeled source domain to learn a classifier for the unlabeled target domain with a different distribution. Previous methods mostly match the distribution between two domains by glo... 详细信息
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Deep Face recognition with Clustering based Domain Adaptation
arXiv
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arXiv 2022年
作者: Wang, Mei Deng, Weihong The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China
Despite great progress in face recognition tasks achieved by deep convolution neural networks (CNNs), these models often face challenges in real world tasks where training images gathered from Internet are different f... 详细信息
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Adaptive Multi-Resolution Feature Fusion for Fine-Grained Visual Classification
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IEEE Transactions on Circuits and systems for Video Technology 2025年
作者: Yang, Yuqi Chang, Dongliang Du, Ruoyi Song, Yi-Zhe Ma, Zhanyu Beijing University of Posts and Telecommunications Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing100876 China Tsinghua University Department of Automation Beijing100084 China University of Surrey SketchX CVSSP GuildfordGU2 7XH United Kingdom
Despite significant progress, the shortage of labeled data and expert knowledge remains a challenge for Fine-grained Visual Classification (FGVC). Some multi-source approaches that incorporate additional modalities, s... 详细信息
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