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This letter proposes a method using convolutional neural networks (CNNs) for airport detection on optical satellite images. To efficiently build a deep CNN with limited satellite image samples, a transfer learning approach had been employed by sharing the common image features of the natural images. To decrease the computing cost, an efficient region proposal method had been proposed based on the...
This paper presents a method for airport detection from optical satellite images using deep convolutional neural networks (CNN). To achieve fast detection with high accuracy, region proposal by searching adjacent parallel line segments has been applied to select candidate fields with potential runways. These proposals were further classified by a CNN model transfer learned from AlexNet to identify...
Pattern recognition is one of the most popular topics in the world today. One of its problems is reducing sample variation for the same class and keeping discrimination for different classes. Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter-correlated quantitative dependent variables. Its goal is to extract...
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