机电工程技术2024，Vol.53Issue(8)：1-6,6.DOI:10.3969/j.issn.1009-9492.2024.08.001
深度学习的实例分割技术研究进展
Research Progress of Instance Segmentation Technology in Deep Learning
摘要
Abstract
The application of deep learning in the field of computer vision achieves significant results in recent years,with new deep learning methods and deep neural network models constantly emerging,and algorithm performance constantly being refreshed.The image instance segmentation method based on deep learning makes significant progress and becomes a powerful tool for image processing.In order to better promote the research and development of deep learning instance segmentation algorithms,a systematic review and summary of the research progress in this field is conducted.Firstly,based on the process and characteristics of image instance segmentation methods,the research progress of image instance segmentation based on deep learning is introduced from a two-stage and a single-stage perspective.Subsequently,commonly used evaluation indicators are introduced.Finally,based on the current shortcomings of instance segmentation technology,feasible solutions are proposed,and the future development of instance segmentation technology is prospected.关键词
计算机视觉/实例分割/深度学习/图像分割/评价指标Key words
computer vision/instance segmentation/deep learning/image segmentation/evaluation indicators分类
信息技术与安全科学引用本文复制引用
孙鹏,孙传聪,徐要要,邹田甜,吴翠杨,甄珍..深度学习的实例分割技术研究进展[J].机电工程技术,2024,53(8):1-6,6.基金项目
山东省教育科学研究项目(19SR001) （19SR001）
山东省人才服务行业协会研究项目(2020094) （2020094）
