Zobrazeno 1 - 10
of 151
pro vyhledávání: '"CHANG Zhigang"'
Autor:
SHI Zhan, CHANG Zhigang
Publikováno v:
Xiehe Yixue Zazhi, Vol 15, Iss 3, Pp 489-497 (2024)
Patients with infections in the department of critical care medicine have complex sources and diverse sites of infection, which may be associated with multiple pathogenic bacteria and have a high rate of drug resistance, posing a significant challeng
Externí odkaz:
https://doaj.org/article/ca4632d4ec0b4e36a47b9b538b3c0437
Autor:
Chang, Zhigang, Zheng, Shibao
Vehicle re-identification (Vehicle ReID) aims at retrieving vehicle images across disjoint surveillance camera views. The majority of vehicle ReID research is heavily reliant upon supervisory labels from specific human-collected datasets for training
Externí odkaz:
http://arxiv.org/abs/2410.21667
Autor:
Hao, Jiaxing, Wang, Yanxi, Chang, Zhigang, Gao, Hongmin, Cheng, Zihao, Wu, Chen, Zhao, Xin, Fang, Peiye, Muwardi, Rachmat
Gait recognition is a remote biometric technology that utilizes the dynamic characteristics of human movement to identify individuals even under various extreme lighting conditions. Due to the limitation in spatial perception capability inherent in 2
Externí odkaz:
http://arxiv.org/abs/2410.08454
Gait recognition is a rapidly progressing technique for the remote identification of individuals. Prior research predominantly employing 2D sensors to gather gait data has achieved notable advancements; nonetheless, they have unavoidably neglected th
Externí odkaz:
http://arxiv.org/abs/2409.11869
In dyadic speaker-listener interactions, the listener's head reactions along with the speaker's head movements, constitute an important non-verbal semantic expression together. The listener Head generation task aims to synthesize responsive listener'
Externí odkaz:
http://arxiv.org/abs/2307.09821
ideo-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods focus on exploring appearance information, thus, vulnerable against ill
Externí odkaz:
http://arxiv.org/abs/2112.05626
Autor:
Chen, Xiangyu, Fan, Junping, Zhao, Wenxian, Shi, Ruochun, Guo, Nan, Chang, Zhigang, Song, Maifen, Wang, Xuedong, Chen, Yan, Li, Tong, Li, Guang-gang, Su, Longxiang, Long, Yun
Publikováno v:
In Heliyon 15 July 2024 10(13)
Deep hamming hashing has gained growing popularity in approximate nearest neighbour search for large-scale image retrieval. Until now, the deep hashing for the image retrieval community has been dominated by convolutional neural network architectures
Externí odkaz:
http://arxiv.org/abs/2105.01823
To learn the optimal similarity function between probe and gallery images in Person re-identification, effective deep metric learning methods have been extensively explored to obtain discriminative feature embedding. However, existing metric loss lik
Externí odkaz:
http://arxiv.org/abs/1911.07273
Deep convolutional neural networks (CNNs) have demonstrated dominant performance in person re-identification (Re-ID). Existing CNN based methods utilize global average pooling (GAP) to aggregate intermediate convolutional features for Re-ID. However,
Externí odkaz:
http://arxiv.org/abs/1803.08580