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Sparse matrix classification on imbalanced datasets using convolutional neural networks
This paper deals with the class imbalance problem in the context of the automatic selection of the best storage format for a sparse matrix with the aim of maximizing the performance of the sparse matrix vector multiplication ...
Dual-Window Superpixel Data Augmentation for Hyperspectral Image Classification
Deep learning (DL) has been shown to obtain superior results for classification tasks in the field of remote sensing hyperspectral imaging. Superpixel-based techniques can be applied to DL, significantly decreasing training ...