Výsledky vyhledávání - "Zhang jiayuan"

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REGNet V2: End-to-End REgion-based Grasp Detection Network for Grippers of Different Sizes in Point Clouds

Autor: Zhao, Binglei, Wang, Han, Tang, Jian, Ma, Chengzhong, Zhang, Hanbo, Zhang, Jiayuan, Lan, Xuguang, Chen, Xingyu

Grasping has been a crucial but challenging problem in robotics for many years. One of the most important challenges is how to make grasping generalizable and robust to novel objects as well as grippers in unstructured environments. We present \regne

Externí odkaz: http://arxiv.org/abs/2410.09431

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DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations

Autor: Zhu, Guogang, Liu, Xuefeng, Niu, Jianwei, Tang, Shaojie, Wu, Xinghao, Zhang, Jiayuan

In personalized federated learning (PFL), it is widely recognized that achieving both high model generalization and effective personalization poses a significant challenge due to their conflicting nature. As a result, existing PFL methods can only ma

Externí odkaz: http://arxiv.org/abs/2407.17754

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Akademický článek

Abnormal topological structure of structural covariance networks based on fractal dimension in noise induced hearing loss

Autor: Wang Liping, Lv Minghui, Zhang jiayuan, Wang Aijie, Huang Ranran, Zhang Zengcai, Zhang Guowei

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)

Abstract The topological attributes of structural covariance networks (SCNs) based on fractal dimension (FD) and changes in brain network connectivity were investigated using graph theory and network-based statistics (NBS) in patients with noise-indu

Externí odkaz: https://doaj.org/article/da5d2d2df5d14028a1911bc72d00acea

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MMRDN: Consistent Representation for Multi-View Manipulation Relationship Detection in Object-Stacked Scenes

Autor: Wang, Han, Zhang, Jiayuan, Wan, Lipeng, Chen, Xingyu, Lan, Xuguang, Zheng, Nanning

Manipulation relationship detection (MRD) aims to guide the robot to grasp objects in the right order, which is important to ensure the safety and reliability of grasping in object stacked scenes. Previous works infer manipulation relationship by dee

Externí odkaz: http://arxiv.org/abs/2304.12592

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FishFuzz: Throwing Larger Nets to Catch Deeper Bugs

Autor: Zheng, Han, Zhang, Jiayuan, Huang, Yuhang, Ren, Zezhong, Wang, He, Cao, Chunjie, Zhang, Yuqing, Toffalini, Flavio, Payer, Mathias

Greybox fuzzing is the de-facto standard to discover bugs during development. Fuzzers execute many inputs to maximize the amount of reached code. Recently, Directed Greybox Fuzzers (DGFs) propose an alternative strategy that goes beyond "just" covera

Externí odkaz: http://arxiv.org/abs/2207.13393

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