基于无锚检测网络的分拣机器人隐蔽目标识别方法

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-08-29 DOI:10.1080/0952813x.2024.2383647

Fuzhi Wang, Changlin Song

引用次数: 0

摘要

工业智能化的快速发展促进了分拣机器人的重要性，但分拣任务的缺点也逐渐显露出来。分拣机器人的目标检测能力是分拣任务的关键。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Occlusive target recognition method of sorting robot based on anchor-free detection network

The rapid development of industry intelligence has promoted the importance of sorting robots, but the shortcomings of sorting tasks are also gradually obvious. The target detection of the sorting r...

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来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving