Novel Class Reasoning Model Towards Covered Area in Given Image Based on InformedKnowledge Graph Reasoning and Multi-agent Collaboration

• Published in: Ji suan ji ke xue Vol. 50; no. 1; pp. 243 - 252
• Main Author: RONG Huan, QIAN Minfeng, MA Tinghuai, SUN Shengjie
• Format: Journal Article
• Language: Chinese
• Published: Editorial office of Computer Science 01.01.2023
• Subjects: knowledge graph reasoning|image object detection|multi-agent reinforcement learning|ddpg
• ISSN: 1002-137X
• DOI: 10.11896/jsjkx.220700112

Object detection is one of the most popular directions in computer vision,which is widely used in military,medical and other important fields.However,most object detection models can only recognize visible objects.There are often covered(invisible) target objects in pictures in daily life.It is difficult for existing object detection models to show ideal detection performance for covered objects in pictures.Therefore,this paper proposes a novel class reasoning model towards covered area in given image based on informed knowledge graph reasoning and multi-agent collaboration(IMG-KGR-MAC).Specifically,first,IMG-KGR-MAC constructs a global prior knowledge graph according to the visible objects of all pictures in a given picture library and the positional relationship between them.At the same time,according to the objects contained in the pictures themselves and their positional relationships,picture knowledge graphs are established for each picture respectively.The covered objects information in each picture is