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1,005 results on '"Zhang, Tianzhu"'

212. Key technologies in the teleoperation of the Chang’e-5 lunar sampling

Author

LIU, ChuanKai, primary, LI, Jian, additional, ZHANG, TianZhu, additional, LIU, Qian, additional, HUANG, ZeYuan, additional, ZHANG, JiTao, additional, GAO, YuHui, additional, YU, TianYi, additional, ZHANG, Kuan, additional, CHANG, TianYu, additional, WU, Jie, additional, YANG, Cheng, additional, LI, GuiLiang, additional, DENG, JiaCheng, additional, XU, NanQing, additional, and FENG, XiaoMeng, additional

Published
2021
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223. Detection of human respiratory viruses among hospitalized children aged ≤5 years in Wuhan (China), from January to May 2020

Author

Hao, Mengchan, primary, Zhu, Yaqi, additional, Fan, Sanling, additional, Wu, Xiaoxue, additional, Hu, Juefu, additional, Wu, Ke, additional, Liu, Zhi, additional, Xi, Jinou, additional, Zhao, Yaoyao, additional, Zhang, Tianzhu, additional, Xia, Jianbo, additional, Wu, Chunchen, additional, and Chen, Jianjun, additional

Published
2021
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224. Inference of virtual network functions' state via analysis of the CPU behavior

Author

Shelbourne, Charles, Linguaglossa, Leonardo, Zhang, Tianzhu, Lipani, Aldo, British Petroleum, Télécom Paris, Nokia Bell Labs, and University College of London [London] (UCL)

Subjects
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

231. Defects inducing anomalous exciton kinetics in monolayer WS2

Author

Li, Zhe, primary, Zeng, Yan, additional, Ou, Zhenwei, additional, Zhang, Tianzhu, additional, Du, Rongguang, additional, Wu, Ke, additional, Guo, Quanbing, additional, Jiang, Wei, additional, Xu, Yuhao, additional, Li, Tao, additional, Min, Tai, additional, Wang, Ti, additional, and Xu, Hongxing, additional

Published
2021
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238. Uncertainty Guided Collaborative Training for Weakly Supervised and Unsupervised Temporal Action Localization

Author

Yang, Wenfei, Zhang, Tianzhu, Zhang, Yongdong, and Wu, Feng

Abstract

In weakly supervised (WSAL) and unsupervised temporal action localization (UAL), the target is to simultaneously localize temporal boundaries and identify category labels of actions with only video-level category labels (WSAL) or category numbers in a dataset (UAL) during training. Among existing methods, attention based methods have achieved superior performance in both tasks by highlighting action segments with foreground attention weights. However, without the segment-level supervision on the attention weight learning, the quality of the attention weight hinders the performance of these methods. In this paper, we propose a novel Uncertainty Guided Collaborative Training (UGCT) strategy to alleviate this problem, which mainly includes two key designs: (1) The first design is an online pseudo label generation module, in which the RGB and FLOW streams work collaboratively to learn from each other. (2) The second design is an uncertainty aware learning module, which can mitigate the noise in the generated pseudo labels. These two designs work together to promote the model performance effectively and efficiently by exchanging information between RGB and FLOW streams. Extensive experimental results on two benchmark datasets with three attention based methods demonstrate the effectiveness of the proposed method, e.g, more than 7.0% performance gain for mAP@IoU=0.5 on THUMOS14 dataset.

Published
2023
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239. Task-Aware Weakly Supervised Object Localization With Transformer

Author

Meng, Meng, Zhang, Tianzhu, Zhang, Zhe, Zhang, Yongdong, and Wu, Feng

Abstract

Weakly supervised object localization (WSOL) aims to predict both object locations and categories with only image-level class labels. However, most existing methods rely on class-specific image regions for localization, resulting in incomplete object localization. To alleviate this problem, we propose a novel end-to-end task-aware framework with a transformer encoder-decoder architecture (TAFormer) to learn class-agnostic foreground maps, including a representation encoder, a localization decoder, and a classification decoder. The proposed TAFormer enjoys several merits. First, the designed three modules can effectively perform class-agnostic localization and classification in a task-aware manner, achieving remarkable performance for both tasks. Second, an optimal transport algorithm is proposed to provide pixel-level pseudo labels to online refine foreground maps. To the best of our knowledge, this is the first work by exploring a task-aware framework with a transformer architecture and an optimal transport algorithm to achieve accurate object localization for WSOL. Extensive experiments with four backbones on two standard benchmarks demonstrate that our TAFormer achieves favorable performance against state-of-the-art methods. Furthermore, we show that the proposed TAFormer provides higher robustness against adversarial attacks and noisy labels.

Published
2023
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243. Additional file 1 of Long noncoding RNA PVT1 promotes breast cancer proliferation and metastasis by binding miR-128-3p and UPF1

Author

Liu, Shuiyi, Chen, Weiqun, Hu, Hui, Zhang, Tianzhu, Wu, Tangwei, Li, Xiaoyi, Li, Yong, Kong, Qinzhi, Lu, Hongda, and Lu, Zhongxin

Subjects
skin and connective tissue diseases
Abstract

Additional file 1: table: Association between PVT1 expression and the subtypes of breast cancer patients (all female). Figure: si-PVT1 and sh-UPF1 knockdown efficiency in Hs578t and MCF-7 cells. (A) Western blot assays for FOXQ1 and UPF1 in Hs578t and MCF-7 cells. (B) Western blot assays for UPF1 in Hs578t and MCF-7 cells.

Published
2021
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