Zobrazeno 1 - 10
of 616
pro vyhledávání: '"Deng, Jingjing"'
Unmanned Aerial Vehicle (UAV) swarms are increasingly deployed in dynamic, data-rich environments for applications such as environmental monitoring and surveillance. These scenarios demand efficient data processing while maintaining privacy and secur
Externí odkaz:
http://arxiv.org/abs/2410.15882
Reliable object grasping is one of the fundamental tasks in robotics. However, determining grasping pose based on single-image input has long been a challenge due to limited visual information and the complexity of real-world objects. In this paper,
Externí odkaz:
http://arxiv.org/abs/2410.15879
Vision-Language Models (VLMs) play a crucial role in robotic manipulation by enabling robots to understand and interpret the visual properties of objects and their surroundings, allowing them to perform manipulation based on this multimodal understan
Externí odkaz:
http://arxiv.org/abs/2410.15863
Federated learning is a machine learning paradigm that enables decentralized clients to collaboratively learn a shared model while keeping all the training data local. While considerable research has focused on federated image generation, particularl
Externí odkaz:
http://arxiv.org/abs/2408.17090
Painting classification plays a vital role in organizing, finding, and suggesting artwork for digital and classic art galleries. Existing methods struggle with adapting knowledge from the real world to artistic images during training, leading to poor
Externí odkaz:
http://arxiv.org/abs/2408.01827
Federated learning (FL) is a powerful Machine Learning (ML) paradigm that enables distributed clients to collaboratively learn a shared global model while keeping the data on the original device, thereby preserving privacy. A central challenge in FL
Externí odkaz:
http://arxiv.org/abs/2404.15919
With increasing concerns over data privacy and model copyrights, especially in the context of collaborations between AI service providers and data owners, an innovative SG-ZSL paradigm is proposed in this work. SG-ZSL is designed to foster efficient
Externí odkaz:
http://arxiv.org/abs/2403.09363
This review paper takes a comprehensive look at malicious attacks against FL, categorizing them from new perspectives on attack origins and targets, and providing insights into their methodology and impact. In this survey, we focus on threat models t
Externí odkaz:
http://arxiv.org/abs/2311.16065
Federated Learning (FL) is a widely adopted privacy-preserving machine learning approach where private data remains local, enabling secure computations and the exchange of local model gradients between local clients and third-party parameter servers.
Externí odkaz:
http://arxiv.org/abs/2305.04095
Autor:
Zhu, Junxuan, Wu, Yuanyue, Xue, Chenyi, Zhang, Manman, Zhang, Yiling, Zhang, Xuefei, Zhou, Tianshu, Deng, Jingjing
Publikováno v:
In Chemical Engineering Journal 15 November 2024 500
