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收录类别:SCI
发表日期:2022
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Learning Semantics-Consistent Stripes With Self-Refinement for Person Re-Identification
期刊论文
IEEE Transactions on Neural Networks and Learning Systems, 2022, 页码: 1-12
作者:
Zhu Kuan
;
Guo Haiyun
;
Liu Songyan
;
Wang Jinqiao
;
Tang Ming
Adobe PDF(4384Kb)
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浏览/下载:160/44
  |  
提交时间:2023/06/08
Hierarchical temporal slot interactions for dialogue state tracking
期刊论文
NEURAL COMPUTING & APPLICATIONS, 2022, 页码: 15
作者:
Qiu, Junyan
;
Lin, Ziqi
;
Zhang, Haidong
;
Yang, Yiping
Adobe PDF(852Kb)
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浏览/下载:258/21
  |  
提交时间:2022/12/27
Dialogue state tracking
Attention mechanism
Task-oriented dialogue system
Slot interaction
Narrowing the Gap: Improved Detector Training With Noisy Location Annotations
期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380
作者:
Wang, Shaoru
;
Gao, Jin
;
Li, Bing
;
Hu, Weiming
Adobe PDF(1489Kb)
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浏览/下载:285/38
  |  
提交时间:2022/11/14
Annotations
Noise measurement
Detectors
Task analysis
Training
Object detection
Degradation
Object detection
noisy label
Bayesian estimation
teacher-student learning
Cross-Batch Hard Example Mining With Pseudo Large Batch for ID vs. Spot Face Recognition
期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 3224-3235
作者:
Tan, Zichang
;
Liu, Ajian
;
Wan, Jun
;
Liu, Hao
;
Lei, Zhen
;
Guo, Guodong
;
Li, Stan Z.
Adobe PDF(10124Kb)
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浏览/下载:296/7
  |  
提交时间:2022/07/25
Face recognition
Training
Measurement
Graphics processing units
Deep learning
Logic gates
Feature extraction
Face recognition
ID vs spot
deep learning
cross-batch hard example mining
pseudo large batch
Toward few-shot domain adaptation with perturbation-invariant representation and transferable prototypes
期刊论文
FRONTIERS OF COMPUTER SCIENCE, 2022, 卷号: 16, 期号: 3, 页码: 11
作者:
Fan, Junsong
;
Wang, Yuxi
;
Guan, He
;
Song, Chunfeng
;
Zhang, Zhaoxiang
Adobe PDF(4804Kb)
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浏览/下载:331/56
  |  
提交时间:2022/06/10
domain adaptation
semantic segmentation
An Efficient Sampling-Based Attention Network for Semantic Segmentation
期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 2850-2863
作者:
He, Xingjian
;
Liu, Jing
;
Wang, Weining
;
Lu, Hanqing
Adobe PDF(3252Kb)
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浏览/下载:399/80
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提交时间:2022/06/10
Stochastic processes
Sampling methods
Semantics
Image segmentation
Computational complexity
Pattern recognition
Convolution
Semantic segmentation
stochastic sampling-based attention
deterministic sampling-based attention
Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 3, 页码: 1228-1241
作者:
Zhu, Yuanheng
;
Zhao, Dongbin
Adobe PDF(2838Kb)
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浏览/下载:252/12
  |  
提交时间:2022/06/10
Games
Nash equilibrium
Mathematical model
Markov processes
Convergence
Dynamic programming
Training
Deep reinforcement learning (DRL)
generalized policy iteration (GPI)
Markov game (MG)
Nash equilibrium
Q network
zero sum
Towards More Discriminative and Robust Iris Recognition by Learning Uncertain Factors
期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2022, 卷号: 17, 页码: 865-879
作者:
Wei, Jianze
;
Huang, Huaibo
;
Wang, Yunlong
;
He, Ran
;
Sun, Zhenan
Adobe PDF(8736Kb)
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浏览/下载:344/58
  |  
提交时间:2022/06/06
Iris recognition
Uncertainty
Training
Task analysis
Computational modeling
Feature extraction
Probabilistic logic
Iris recognition
cross-sensor recognition
uncertainty learning
curriculum learning
From Individual to Whole: Reducing Intra-class Variance by Feature Aggregation
期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2022, 卷号: 130, 期号: 3, 页码: 800-819
作者:
Zhang, Zhaoxiang
;
Luo, Chuanchen
;
Wu, Haiping
;
Chen, Yuntao
;
Wang, Naiyan
;
Song, Chunfeng
Adobe PDF(1762Kb)
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浏览/下载:317/44
  |  
提交时间:2022/06/06
Feature aggregation
Deep learning
Intra-class variance
Person re-identification
Video object detection
Partial Domain Adaptation by Progressive Sample Learning of Shared Classes
期刊论文
Neural Processing Letters, 2022, 卷号: 0, 期号: 0, 页码: 0
作者:
Lei, Tian
;
Yongqiang, Tang
;
Wensheng, Zhang
Adobe PDF(912Kb)
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浏览/下载:228/63
  |  
提交时间:2022/04/06
Partial domain adaptation
Domain adaptation
Transfer learning
Self-paced learning
Low-dimensional subspace learning