Skip to content
naulon
Not checkedNot checked for notices yet.

Research status of damage identification algorithm based on deep learning

Denghui Zhu, Lizhong Song, yuan Feng and 1 more

E3S Web of Conferences · 2021

doi:10.1051/e3sconf/202123304039 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

One of the core tasks of computer vision is target detection. With the rapid development of deep learning, target detection technology based on deep learning has become the mainstream algorithm in this field. As one of the main application fields, damage identification has achieved important development in the past decade. This paper systematically summarizes the research progress of damage identification algorithm based on deep learning, analyzes the advantages and disadvantages of each algorithm and its detection results on voc2007, voc2012 and coco data sets. Finally, the main contents of this paper are summarized, and the research prospect of deep learning based damage identification algorithm is prospect.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.