喧闹 发表于 2025-3-23 11:25:20
Jane Clarkwever, almost all of these studies only focus on discrete or continuous action space and there are few works having ever applied multi-agent deep reinforcement learning (MADRL) to discrete-continuous hybrid action space which is common in practice problems. In this paper, two novel approaches are prHabituate 发表于 2025-3-23 16:14:44
http://reply.papertrans.cn/99/9831/983063/983063_12.pngAmenable 发表于 2025-3-23 21:41:31
Jane Clarkion information. Contextual information is a significant factor in the task of recognizing image action, which is inseparable from a predefined action class. And the existing research strategy does not ensure adequate use of contextual information. To address this issue, we propose a Contextual Enha大洪水 发表于 2025-3-24 00:18:25
http://reply.papertrans.cn/99/9831/983063/983063_14.png反话 发表于 2025-3-24 03:09:55
Jane Clarkcrepancy. Existing methods mainly focus on bridging the relation between modalities by shared representation learning in the common embedding space. However, due to the outliers, these methods often struggle to build compact clustering subspaces. Besides, these methods also suffer from modality imbaallergen 发表于 2025-3-24 07:34:52
http://reply.papertrans.cn/99/9831/983063/983063_16.pngheirloom 发表于 2025-3-24 12:00:20
Jane Clarkowever, domain adaptation presents a significant challenge due to the impact of weather, lighting, and scene context on object detection models. To address this issue, we propose a new method that utilizes pseudo-labels. Our approach involves two modules: the Category-Adversarial-Adaptive (CAA) and最初 发表于 2025-3-24 18:33:46
http://reply.papertrans.cn/99/9831/983063/983063_18.png有组织 发表于 2025-3-24 22:39:17
http://reply.papertrans.cn/99/9831/983063/983063_19.pngechnic 发表于 2025-3-25 02:09:08
http://reply.papertrans.cn/99/9831/983063/983063_20.png