Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …

Images are susceptible to various kinds of noises, which corrupt the pictorial information
stored in the images. Image de-noising has become an integral part of the image processing …

Deep learning has gained significant interest in image denoising, but there are notable
distinctions in the types of deep learning methods used. Discriminative learning is suitable …

Color image restoration is one of the basic tasks in pattern recognition. Unlike grayscale
image, each color image has three channels in the RGB color space. Due to the inner …

Sea subsurface temperature, an essential component of aquatic wildlife, underwater
dynamics, and heat transfer with the sea surface, is affected by global warming in climate …

Biomedical signals are frequently contaminated by colored noise; consequently, noise
recognition and reduction are critical to biomedical systems. Conventional techniques have …

In this paper, a novel approach to the mixed Gaussian and impulsive noise reduction in
color images is proposed. The described denoising framework is based on the Non-Local …

A sports training video classification model based on deep learning is studied for targeting
low classification accuracy caused by the randomness of objective movement in sports …

Existing image and video denoising algorithms have focused on removing homogeneous
Gaussian noise. However, this assumption with noise modeling is often too simplistic for the …

In recent years there has been growing interest in the study of depth map's impulse noise
detection and removal. The Rank-ordered Absolute Differences (ROAD) based on …