Mixture separability loss in a deep convolutional network for image classification - Do, Trung Dung; Jin, Cheng-Bin; Nguyen, Van Huan; Kim, Hakil (IET image processing, 2019)
Keywords: applying cross‐entropy loss; between‐class loss; Canadian institute for advanced research; computer vision; convolutional layers; deep convolutional network; entropy; feedforward neural nets; image classification; image representation; inter‐class images; intra‐class images; learning (artificial intelligence); loss function; machine learning; mixture separability loss; MSL; network structures; novel cost function; Research Article; self‐collected Inha computer vision lab gender dataset; street view house number; training images; well‐known networks; within‐class loss; inter-class images; within-class loss; deep convolutional network; well-known networks; image classification; street view house number; self-collected Inha computer vision lab gender dataset; MSL; training images; novel cost function; machine learning; loss function; entropy; intra-class images; between-class loss; image representation; computer vision; mixture separability loss; Canadian institute for advanced research; learning (artificial intelligence); convolutional layers; network structures; feedforward neural nets; applying cross-entropy loss