Convolutional neural networks (CNNs) have gained prominence in the research literature
on image classification over the last decade. One shortcoming of CNNs, however, is their …

Several techniques have recently been proposed to extract the features of an image.
Feature extraction is one of the most important steps in various image processing and …

Convolutional Neural Networks (CNN) have brought spectacular improvements in several
fields of machine vision including object, scene and face recognition. Nonetheless, the …

The land cover reconstruction from monochromatic historical aerial images is a challenging
task that has recently attracted an increasing interest from the scientific community with the …

Image classification is the process of assigning a category/class to an image. It has gained
much importance in the recent years because of its real-time applications in object tracking …

In this study, we propose to address the difficult task of bark recognition in the wild using
computationally efficient and compact feature vectors. We introduce two novel generic …

Color texture classification aims to recognize patterns by the analysis of their colors and their
textures. This process requires using descriptors to represent and discriminate the different …

Texture description is a challenging problem with color images. Despite some attempts to
include colors in local binary patterns (LBPs), no proposal has emerged as a color …

This paper addresses the task of material and natural texture classification. We propose a
new discriminant color texture descriptor based on local pattern encoding scheme using …

Tree species identification and tree organ segmentation using images are challenging
problems that are useful in many forestry-related tasks. In this paper, the urban street tree …