Zobrazeno 1 - 10
of 503
pro vyhledávání: '"Zhang, SenLin"'
This paper presents a general scheme for enhancing the convergence and performance of DETR (DEtection TRansformer). We investigate the slow convergence problem in transformers from a new perspective, suggesting that it arises from the self-attention
Externí odkaz:
http://arxiv.org/abs/2407.11699
The primary objective of Multi-Agent Pathfinding (MAPF) is to plan efficient and conflict-free paths for all agents. Traditional multi-agent path planning algorithms struggle to achieve efficient distributed path planning for multiple agents. In cont
Externí odkaz:
http://arxiv.org/abs/2407.10403
DETR-like methods have significantly increased detection performance in an end-to-end manner. The mainstream two-stage frameworks of them perform dense self-attention and select a fraction of queries for sparse cross-attention, which is proven effect
Externí odkaz:
http://arxiv.org/abs/2403.16131
This article introduces a five-tiered route planner for accessing multiple nodes with multiple autonomous underwater vehicles (AUVs) that enables efficient task completion in stochastic ocean environments. First, the pre-planning tier solves the sing
Externí odkaz:
http://arxiv.org/abs/2311.06579
Cooperative online scalar field mapping is an important task for multi-robot systems. Gaussian process regression is widely used to construct a map that represents spatial information with confidence intervals. However, it is difficult to handle coop
Externí odkaz:
http://arxiv.org/abs/2309.10311
Publikováno v:
IEEE Robotics and Automation Letters, 2023
In this paper, we consider improving the efficiency of information-based autonomous robot exploration in unknown and complex environments. We first utilize Gaussian process (GP) regression to learn a surrogate model to infer the confidence-rich mutua
Externí odkaz:
http://arxiv.org/abs/2309.05200
This paper investigates the problem of distributed target tracking via underwater wireless sensor networks (UWSNs) with fading channels. The degradation of signal quality due to wireless channel fading can significantly impact network reliability and
Externí odkaz:
http://arxiv.org/abs/2308.04013
In this paper, physics-informed neural network (PINN) based on characteristic-based split (CBS) is proposed, which can be used to solve the time-dependent Navier-Stokes equations (N-S equations). In this method, The output parameters and correspondin
Externí odkaz:
http://arxiv.org/abs/2304.10717
This paper concerns realizing highly efficient information-theoretic robot exploration with desired performance in complex scenes. We build a continuous lightweight inference model to predict the mutual information (MI) and the associated prediction
Externí odkaz:
http://arxiv.org/abs/2301.00523
Autor:
Zhang, Senlin1 (AUTHOR), Ling, Jing1 (AUTHOR), Cui, Kai1 (AUTHOR), Zhan, Shihong2 (AUTHOR), Zheng, Jiajia1 (AUTHOR), Wang, Wenyi1 (AUTHOR), Fan, Junjie1 (AUTHOR) jjiefan@126.com, Hu, Shaoyan1 (AUTHOR) hushaoyan@suda.edu.cn
Publikováno v:
Hematology. Dec2024, Vol. 29 Issue 1, p1-6. 6p.
