Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image

This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images. Firstly, the application effects of R-CNN (Region-Convolutional Neural Network), FRCN (Fast Region-Convolu...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	PloS one Jg. 16; H. 10; S. e0259283
Hauptverfasser:	Wu, Wentong, Liu, Han, Li, Lingling, Long, Yilin, Wang, Xiaodong, Wang, Zhuohua, Li, Jinglun, Chang, Yi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 29.10.2021 Public Library of Science (PLoS)
Schlagworte:	Accuracy Adaptability Algorithms Analysis Artificial intelligence Artificial neural networks Biology and Life Sciences Computer and Information Sciences Computer architecture Datasets Earth Sciences Engineering and Technology Feature extraction Feature recognition Genetic algorithms Geographic information systems Image detection Neural networks Neural Networks, Computer Object recognition Pattern Recognition, Automated - methods Pattern Recognition, Automated - standards Physical Sciences R&D Remote sensing Research & development Research and Analysis Methods Satellite Imagery - methods Satellite Imagery - standards Satellites Signal processing Social Sciences Storage tanks Target detection Workloads China
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!