深度学习及其在图像物体分类与检测中的应用综述
刘栋; 李素; 曹志冬
Source Publication计算机科学
2016
Volume43Issue:12Pages:13-23
Abstract传统的图像物体分类与检测算法及策略难以满足图像视频大数据在处理效率、性能和智能化等方面所提出的要求。深度学习通过模拟类似人脑的层次结构建立从低级信号到高层语义的映射,以实现数据的分级特征表达,具有强大的视觉信息处理能力,成为应对这一挑战的前沿技术和国内外研究热点。首先论述了深度学习的起源、发展历程及理论体系;然后分别围绕图像物体分类和检测,总结了近年来深度学习在视觉领域的发展;最后对深度学习及其在视觉领域目前存在的诸多问题以及后续的研究方向进行了分类探讨。
Other AbstractApplication in the field of video image data fast extension of the traditional image object classification and detection algorithms and strategies make enormous challenge faced with the efficiency, performance and intelligence. Therefore, the depth of learning with excellent visual information processing ability has become the research hotspot in the field. First of all, this paper summarizes the rise and development of the depth of learning. Then, based on the latest research progress, we deeply discuss the theoretical system; and then around the objects in image classification and detection, discussion and summary in recent years the depth of learning in the visual field of application and development. Finally, for deep learning and image classification and detection of existing many problems and challenges and follow-up research directions were discussed.
Keyword深度学习 特征表达 图像物体分类
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20188
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding Author曹志冬
Affiliation1.北京工商大学计算机与信息工程学院食品安全大数据技术北京市重点实验室
2.中国科学院自动化研究所复杂系统管理与控制国家重点实验室
Recommended Citation
GB/T 7714
刘栋,李素,曹志冬. 深度学习及其在图像物体分类与检测中的应用综述[J]. 计算机科学,2016,43(12):13-23.
APA 刘栋,李素,&曹志冬.(2016).深度学习及其在图像物体分类与检测中的应用综述.计算机科学,43(12),13-23.
MLA 刘栋,et al."深度学习及其在图像物体分类与检测中的应用综述".计算机科学 43.12(2016):13-23.
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