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HySARNet: a hybrid machine learning approach to synthetic aperture radar automatic target recognition
Radar target recognition using wavelet-based features extracted from compressively sensed signatures
Characterization of CNN classifier performance with respect to variation in optical contrast, using synthetic electro-optical data
Neural network classification of degraded imagery using soft labels: towards human-level performance with “accurate” likelihoods?
Transfer learning for aided target recognition: comparing deep learning to other machine learning approaches
Applying image processing techniques to security data: towards cyber target recognition (Conference Presentation)
Real-time beacon identification using linear and kernel (non-linear) Support Vector Machine, Multiple Kernel Learning (MKL), and Light Detection and Ranging (LIDAR) 3D data