Texture analysis is used in a very broad range of fields and applications, from texture
classification (eg, for remote sensing) to segmentation (eg, in biomedical imaging), passing …

In this paper, the unsupervised autoencoder learning for automated defect detection in
manufacturing is evaluated, where only the defect-free samples are required for the model …

This article presents a deep learning scheme for automatic defect detection in material
surfaces. The success of deep learning model training is generally determined by the …

Melanoma is the deadliest kind of skin cancer. However, it's hard to identify melanoma
during its early to mid stages by visual examination. So, there is a call for an automated …

Abstract Local Binary Pattern (LBP) is widely used in texture classification because of its
powerful capability to extract texture features of a center pixel. However, LBP has three main …

In the aerospace industry, automated fibre laying processes are often applied for
economical composite part fabrication. Unfortunately, the current mandatory visual quality …

This paper presents an automatic recognition system for classifying stones belonging to
different Calabrian quarries (Southern Italy). The tool for stone recognition has been …

In this paper, a novel rotation and scale invariant approach for texture classification based
on Gabor filters has been proposed. These filters are designed to capture the visual content …

Ground military target recognition plays a crucial role in unmanned equipment and gras**
the battlefield dynamics for military applications, but is disturbed by low-resolution and noisy …

Purpose Precise diagnosis and identification of early dental caries facilitates timely
intervention and reverses the progression of the disease. Develo** an objective, accurate …