Impact of motion blur on recognition rates of CNN-based TOD classifier models
Daniel Wegner,
Stefan Keßler
Abstract:This work investigates the impact of various types of motion blur on the recognition rate of triangle orientation discrimination (TOD) models. Models based on convolutional neural networks (CNNs) have been proposed as an automated and faster alternative to observer experiments for range performance assessment. They may also give insights into the impact of system degradations on the performance of automated target recognition algorithms. However, the effects of many image distortions on the recognition rate of… Show more
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