Title
Self-supervised cross-iterative clustering for unlabeled plant disease images
Abstract
•Developing an under-clustering algorithm to extract the most possible clusters.•Involving heuristics and deep models in the framework for clustering effectiveness.•Making up the deep learning research gap in the field of plant disease annotation.
Year
DOI
Venue
2021
10.1016/j.neucom.2021.05.066
Neurocomputing
Keywords
DocType
Volume
Pattern Recognition,Clustering,Dimensional analysis and similarity,Self-supervised learning,Automated annotation
Journal
456
ISSN
Citations 
PageRank 
0925-2312
1
0.35
References 
Authors
0
6
Name
Order
Citations
PageRank
Uno Fang110.35
Jianxin Li244348.67
Xuequan Lu36417.63
Longxiang Gao431.74
Mumtaz Ali517112.30
Yong Xiang6113793.92