@ARTICLE{8708947,
author={K. {Jia} and J. {Lin} and M. {Tan} and D. {Tao}},
journal={IEEE Transactions on Image Processing},
title={Deep Multi-View Learning Using Neuron-Wise Correlation-Maximizing Regularizers},
year={2019},
volume={28},
number={10},
pages={5121-5134},
keywords={feature extraction;image classification;image colour analysis;image fusion;learning (artificial intelligence);object recognition;deep multiview learning;regularized network training;CorrReg;practical multiview learning problems;multiview-based 3D object recognition;individual modalities;neuron-wise correlation-maximizing regularizers;machine learning problems;deep multiview networks;generic deep neural networks;intermediate network layers;end-to-end networks;multiview learning criteria;efficient neuron-wise correlation-maximizing regularizer;correlation-regularized network layer;convolutional fusion layers;generic DNN;RGB-D object recognition;RGB-D scene recognition;Training;Neurons;Task analysis;Correlation;Benchmark testing;Object recognition;Feature extraction;Multi-view learning;deep learning;regularization;normalization;canonical correlation analysis},
doi={10.1109/TIP.2019.2912356},
ISSN={},
month={Oct},}