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Abstract: In this work, we propose a supervised framework for spectral unmixing of binary intimate mixtures. The core idea is based on geodesic distance measurements and regression to estimate the ...

Abstract: Through truncating the weights and activations of a deep neural network, conventional binary quantization imposes limitations on the representation capability of the network parameters, ...