Multiple-Oriented and Small Object Detection with Convolutional Neural Networks for Aerial Image

Multiple-Oriented and Small Object Detection with Convolutional Neural Networks for Aerial Image

Detecting objects in aerial images is a challenging task due to multiple orientations and relatively small size of the objects. Although many traditional detection models have demonstrated an acceptable performance by using the imagery pyramid and multiple templates in a sliding-window manner, such...

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Bibliographic Details
Main Authors: Chao Chen, Jiandan Zhong, Yi Tan
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Remote Sensing
Subjects:
object detection
aerial image
convolutional neural network
deep learning
multiple orientations
Online Access:https://www.mdpi.com/2072-4292/11/18/2176

Internet

https://www.mdpi.com/2072-4292/11/18/2176

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