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17 July 1998 Detection of vehicles in infrared imagery using shared-weight neural network feature detectors
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Abstract
In this paper, we discuss the possibility of using artificial neural networks (ANNs) as feature detectors in automatic target recognition (ATR). The goal is to discern a vehicle in an infrared image. We train ANNs to recognize the most easily recognizable parts of the vehicles, the wheels. The specific ANNs we use, shared weight ANNs, are especially adept at such an image recognition task due to their specialized architecture. The feature detection stage results in an image containing in each pixel the output of the ANN, indicating its confidence in the classification. We can then use a simple sequence of image processing algorithms on this image to find peaks and, by counting the number of these peaks, vehicles. This system is tested on sensitivity to scale differences and background clutter and is shown to perform quite well.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dick de Ridder, Klamer Schutte, and Piet B. W. Schwering "Detection of vehicles in infrared imagery using shared-weight neural network feature detectors", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); https://doi.org/10.1117/12.327104
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