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Satellite Image Classification with Deep Learning
Yet traditional object detection and classification algorithms are too inaccurate and unreliable to solve the problem.
A Comparison of Deep Learning Object Detection Models for Satellite Imagery
In this work, we compare the detection accuracy and speed of several state-of-the-art models for the task of detecting oil and gas fracking wells and small cars in commercial electro-optical satellite imagery.
Globally-scalable Automated Target Recognition (GATR)
On a single GPU it processes imagery at a rate of over 16 square km/sec (or more than 10 Mpixels/sec), and it requires only two hours to search the entire state of Pennsylvania for gas fracking wells.
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