Zobrazeno 1 - 10
of 9 834
pro vyhledávání: '"An, Yiyuan"'
Autonomous underwater vehicles (AUVs) are valuable for ocean exploration due to their flexibility and ability to carry communication and detection units. Nevertheless, AUVs alone often face challenges in harsh and extreme sea conditions. This study i
Externí odkaz:
http://arxiv.org/abs/2409.02444
Leveraging large language models (LLMs) for designing reward functions demonstrates significant potential. However, achieving effective design and improvement of reward functions in reinforcement learning (RL) tasks with complex custom environments a
Externí odkaz:
http://arxiv.org/abs/2409.02428
Ocean exploration utilizing autonomous underwater vehicles (AUVs) via reinforcement learning (RL) has emerged as a significant research focus. However, underwater tasks have mostly failed due to the observation delay caused by acoustic communication
Externí odkaz:
http://arxiv.org/abs/2409.02424
Current road damage detection methods, relying on manual inspections or sensor-mounted vehicles, are inefficient, limited in coverage, and often inaccurate, especially for minor damages, leading to delays and safety hazards. To address these issues a
Externí odkaz:
http://arxiv.org/abs/2409.01604
Autor:
An, Wei, Bi, Xiao, Chen, Guanting, Chen, Shanhuang, Deng, Chengqi, Ding, Honghui, Dong, Kai, Du, Qiushi, Gao, Wenjun, Guan, Kang, Guo, Jianzhong, Guo, Yongqiang, Fu, Zhe, He, Ying, Huang, Panpan, Li, Jiashi, Liang, Wenfeng, Liu, Xiaodong, Liu, Xin, Liu, Yiyuan, Liu, Yuxuan, Lu, Shanghao, Lu, Xuan, Nie, Xiaotao, Pei, Tian, Qiu, Junjie, Qu, Hui, Ren, Zehui, Sha, Zhangli, Su, Xuecheng, Sun, Xiaowen, Tan, Yixuan, Tang, Minghui, Wang, Shiyu, Wang, Yaohui, Wang, Yongji, Xie, Ziwei, Xiong, Yiliang, Xu, Yanhong, Ye, Shengfeng, Yu, Shuiping, Zha, Yukun, Zhang, Liyue, Zhang, Haowei, Zhang, Mingchuan, Zhang, Wentao, Zhang, Yichao, Zhao, Chenggang, Zhao, Yao, Zhou, Shangyan, Zhou, Shunfeng, Zou, Yuheng
The rapid progress in Deep Learning (DL) and Large Language Models (LLMs) has exponentially increased demands of computational power and bandwidth. This, combined with the high costs of faster computing chips and interconnects, has significantly infl
Externí odkaz:
http://arxiv.org/abs/2408.14158
Large Language Models (LLMs) have demonstrated potential in Vision-and-Language Navigation (VLN) tasks, yet current applications face challenges. While LLMs excel in general conversation scenarios, they struggle with specialized navigation tasks, yie
Externí odkaz:
http://arxiv.org/abs/2408.11051
The semantic segmentation task in pathology plays an indispensable role in assisting physicians in determining the condition of tissue lesions. With the proposal of Segment Anything Model (SAM), more and more foundation models have seen rapid develop
Externí odkaz:
http://arxiv.org/abs/2408.03651
Partial-Label Learning (PLL) is a typical problem of weakly supervised learning, where each training instance is annotated with a set of candidate labels. Self-training PLL models achieve state-of-the-art performance but suffer from error accumulatio
Externí odkaz:
http://arxiv.org/abs/2407.15036
Watching micro-videos is becoming a part of public daily life. Usually, user watching behaviors are thought to be rooted in their multiple different interests. In the paper, we propose a model named OPAL for micro-video matching, which elicits a user
Externí odkaz:
http://arxiv.org/abs/2407.14741
Process mining, as a high-level field in data mining, plays a crucial role in enhancing operational efficiency and decision-making across organizations. In this survey paper, we delve into the growing significance and ongoing trends in the field of p
Externí odkaz:
http://arxiv.org/abs/2407.11280