Image classification is a very popular machine learning domain in which deep convolutional
neural networks have mainly emerged on such applications. These networks manage to …

As neural networks become able to generate realistic artificial images, they have the
potential to improve movies, music, video games and make the internet an even more …

This study presents a new approach based on shearlet transform for the first time to detect
damages, and compare it with the wavelet, Laplacian pyramid, curvelet, and contourlet …

Clustering aims to group similar objects together while separating dissimilar ones apart.
Thereafter, structures hidden in data can be identified to help understand data in an …

This paper reports some part of modelling and data analysis work carried out within the
frame of a comprehensive project on the web-based development of watershed information …

In this study, an internal fingerprint-guided epidermal thickness of fingertip skin is proposed
for optical image encryption based on optical coherence tomography (OCT) combined with …

Although recent studies have proposed seizure detection algorithms with good sensitivity
performance, there is a remained challenge that they were hard to achieve significantly short …

Current metrics for generative neural networks are biased towards low frequencies, specific
generators, objects from the ImageNet dataset, and value texture more than shape. Many …

A combination of decision tree (DT) and fuzzy logic techniques was used to develop a fuzzy
model for differentiating peanut plant from weeds. Color features and wavelet-based texture …

Abstract Convolutional Neural Networks (CNNs) are known for requiring extensive
computational resources, and quantization is among the best and most common methods for …