Abstract Aerial scene classification is a challenging problem in understanding high-resolution remote sensing images. Most recent aerial approaches are based on Convolutional Neural Networks (CNNs). These CNN models trained large amount of labeled data and the de facto practice to use RGB patches as input networks. However, importance color within deep learning framework yet be investigated for...

Abstract Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of Non-Hodgkin’s Lymphoma, presenting a great challenge for treatment due to its highly heterogeneous nature. DLBCL diagnosed based on microscopy images patient tissue samples. To help gain better understanding DLBCL, we developed an automated computer vision method analyze morphological and color-based information within...

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB col...