An Optimized Deep Neural Network Detecting Small and Narrow Rectangular Objects in Google Earth Images

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 13; pp. 1068 - 1081
• Main Authors: Jiang, Shenlu, Yao, Wei, Wong, Man Sing, Li, Gen, Hong, Zhonghua, Kuc, Tae-Yong, Tong, Xiaohua
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Artificial intelligence; Artificial neural networks; Datasets; Detection; Earth; Feature extraction; Gray scale; Height; Image detection; Image resolution; Imagery; Localization; Machine learning; Meteorological satellites; Neural networks; Object detection; Object recognition; optical image processing; Ratios; Remote sensing; Satellite imagery; Satellites; Spaceborne remote sensing; Task analysis; Testing; Training; Width

Object detection is an important task for rapidly localizing target objects using high-resolution satellite imagery (HRSI). Although deep learning has been shown an efficient means of detection, object detection in HRSI remains problematic due to variations in object scale and size. In this article,...