Open AccessDetection and recognition of objects on aerial photographs using convolutional neural networks
Author(s) -
V. I. Pavlov,
Marina A. Galeeva
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1326/1/012038
Subject(s) - convolutional neural network , artificial intelligence , computer science , aerial photography , computer vision , pattern recognition (psychology) , object detection , artificial neural network , photography , remote sensing , geography , visual arts , art
The article is devoted to the use of neural network methods to solve the problem of detection and classification of small objects on aerial photographs. The architectures of YOLO 2 and YOLO 3 are discussed. The training procedure is described, the obtained results are analyzed. During the work it was shown that the considered architectures can be used to solve the problem of detecting and classifying objects in images obtained as a result of aerial photography.