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Exploring Explicitly Disentangled Features for Domain Generalization
期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 11, 页码: 6360-6373
作者:
Li, Jingwei
;
Li, Yuan
;
Wang, Huanjie
;
Liu, Chengbao
;
Tan, Jie
收藏
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浏览/下载:0/0
  |  
提交时间:2023/12/21
Domain generalization
feature disentanglement
Fourier transform
data augmentation
A Unified Multimodal De- and Re-Coupling Framework for RGB-D Motion Recognition
期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 10, 页码: 11428-11442
作者:
Zhou, Benjia
;
Wang, Pichao
;
Wan, Jun
;
Liang, Yanyan
;
Wang, Fan
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  |  
浏览/下载:6/0
  |  
提交时间:2023/11/16
Spatiotemporal phenomena
Representation learning
Training
Optimization
Task analysis
Three-dimensional displays
Solid modeling
Complement feature
late fusion
motion recognition
RGB-D
video augmentation
Jointing Recurrent Across-Channel and Spatial Attention for Multi-Object Tracking With Block-Erasing Data Augmentation
期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 8, 页码: 4054-4069
作者:
Deng, Keyu
;
Zhang, Congxuan
;
Chen, Zhen
;
Hu, Weiming
;
Li, Bing
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2023/11/17
Multi-object tracking
one shot
multiattention feature learning
block erasing strategy
object occlusions
An effective pest detection method with automatic data augmentation strategy in the agricultural field
期刊论文
SIGNAL IMAGE AND VIDEO PROCESSING, 2022
作者:
Qian, Shaowei
;
Du, Jianming
;
Zhou, Jianan
;
Xie, Chengjun
;
Jiao, Lin
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2022/12/23
Deep learning
Pest detection and recognition
Data augmentation
Computer vision
SAPS: Self-Attentive Pathway Search for weakly-supervised action localization with-action
期刊论文
COMPUTER VISION AND IMAGE UNDERSTANDING, 2021, 卷号: 210, 页码: 9
作者:
Zhang, Xiao-Yu
;
Zhang, Yaru
;
Shi, Haichao
;
Dong, Jing
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  |  
浏览/下载:44/0
  |  
提交时间:2021/11/03
Video understanding
Action localization
Representation learning
Neural architecture search
Background modeling
Underwater real-time target detection based on key frame and model compression
期刊论文
Journal of Physics: Conference Series, 2021, 卷号: 1800, 期号: 1
作者:
Guo,Wei
;
Zhang,Youbo
;
Zhou,Yue
;
Xu,Gaofei
;
Li,Guangwei
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2021/03/23
Obtaining Urban Waterlogging Depths from Video Images Using Synthetic Image Data
期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 6, 页码: 14
作者:
Jiang, Jingchao
;
Qin, Cheng-Zhi
;
Yu, Juan
;
Cheng, Changxiu
;
Liu, Junzhi
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2021/03/23
urban flooding
waterlogging depth
video image
synthetic image data
reference object detection
convolutional neural network
Online Bayesian max-margin subspace learning for multi-view classification and regression
期刊论文
MACHINE LEARNING, 2019, 页码: 31
作者:
He, Jia
;
Du, Changying
;
Zhuang, Fuzhen
;
Yin, Xin
;
He, Qing
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2020/12/10
Multi-view learning
Online learning
Bayesian subspace learning
Max-margin
Classification
Regression
Spontaneous facial expression database for academic emotion inference in online learning
期刊论文
IET COMPUTER VISION, 2019, 卷号: 13, 期号: 3, 页码: 329-337
作者:
Bian, Cunling
;
Zhang, Ya
;
Yang, Fei
;
Bi, Wei
;
Lu, Weigang
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/12/11
learning (artificial intelligence)
neural nets
visual databases
face
recognition
emotion recognition
inference mechanisms
computer aided
instruction
image classification
coefficient
external coders
image
database
convolutional neural network-based algorithm
data
augmentation algorithms
adaptive data augmentation algorithm
inference
performance
spontaneous facial expression database
online learning
learning effect
students
automatic academic emotion inference
facial
expressions
inference algorithm
common academic emotions
video clip
database
1274 video clips
Underwater Object Recognition Based on Deep Encoding-Decoding Network
期刊论文
Journal of Ocean University of China, 2019, 卷号: 18, 期号: 2, 页码: 376-382
作者:
X.H.Wang
;
J.H.Ouyang
;
D.Y.Li
;
G.Zhang
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2020/08/24
deep learning,transfer learning,encoding-decoding,underwater object,object recognition,Oceanography
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