Zobrazeno 1 - 10
of 2 623
pro vyhledávání: '"ZHANG Xiaotong"'
Improving connectivity and completeness are the most challenging aspects of small liver vessel segmentation. It is difficult for existing methods to obtain segmented liver vessel trees simultaneously with continuous geometry and detail in small vesse
Externí odkaz:
http://arxiv.org/abs/2411.00617
Predicting human intent is challenging yet essential to achieving seamless Human-Robot Collaboration (HRC). Many existing approaches fail to fully exploit the inherent relationships between objects, tasks, and the human model. Current methods for pre
Externí odkaz:
http://arxiv.org/abs/2410.00302
Human intelligence possesses the ability to effectively focus on important environmental components, which enhances perception, learning, reasoning, and decision-making. Inspired by this cognitive mechanism, we introduced a novel concept termed relev
Externí odkaz:
http://arxiv.org/abs/2409.13998
Effective human-robot collaboration (HRC) requires the robots to possess human-like intelligence. Inspired by the human's cognitive ability to selectively process and filter elements in complex environments, this paper introduces a novel concept and
Externí odkaz:
http://arxiv.org/abs/2409.07753
Autor:
Xu, Cheng, Zhang, Changtian, Shi, Yuchen, Wang, Ran, Duan, Shihong, Wan, Yadong, Zhang, Xiaotong
Recent advancements in reinforcement learning have made significant impacts across various domains, yet they often struggle in complex multi-agent environments due to issues like algorithm instability, low sampling efficiency, and the challenges of e
Externí odkaz:
http://arxiv.org/abs/2408.11416
The increasing volume of data in relational databases and the expertise needed for writing SQL queries pose challenges for users to access and analyze data. Text-to-SQL (Text2SQL) solves the issues by utilizing natural language processing (NLP) techn
Externí odkaz:
http://arxiv.org/abs/2407.15186
Autor:
Liu, Han, Zhao, Siyang, Zhang, Xiaotong, Zhang, Feng, Wang, Wei, Ma, Fenglong, Chen, Hongyang, Yu, Hong, Zhang, Xianchao
Few-shot and zero-shot text classification aim to recognize samples from novel classes with limited labeled samples or no labeled samples at all. While prevailing methods have shown promising performance via transferring knowledge from seen classes t
Externí odkaz:
http://arxiv.org/abs/2405.03565
Publikováno v:
Revue française de science politique, 2019 Aug 01. 69(4), 758-759.
Externí odkaz:
https://www.jstor.org/stable/26875856
Mine fleet management algorithms can significantly reduce operational costs and enhance productivity in mining systems. Most current fleet management algorithms are evaluated based on self-implemented or proprietary simulation environments, posing ch
Externí odkaz:
http://arxiv.org/abs/2404.00622
Autor:
Liu, Han, Xu, Zhi, Zhang, Xiaotong, Zhang, Feng, Ma, Fenglong, Chen, Hongyang, Yu, Hong, Zhang, Xianchao
Black-box hard-label adversarial attack on text is a practical and challenging task, as the text data space is inherently discrete and non-differentiable, and only the predicted label is accessible. Research on this problem is still in the embryonic
Externí odkaz:
http://arxiv.org/abs/2402.01806