Statistically, image denoising is one of the key pillars of image processing and picture
acquisition, which also is utilized to clear the noisy images. Over the last years, there is an …

This study focused on an innovative practical method using computer vision for particle size
measurement, which serves as a key precursor for predicting the elastic modulus of polymer …

Lung diseases are the third-leading cause of mortality in the world. Due to compromised
lung function, respiratory difficulties, and physiological complications, lung disease brought …

This book introduces the concept of Algogens, a promising integration of generative AI with
traditional algorithms aimed at improving problem-solving techniques across various fields …

State-of-the-art automatic speech recognition models often struggle to capture nuanced
features inherent in accented speech, leading to sub-optimal performance in speaker …

Abstract Background and Objective. Auto-encoders have demonstrated outstanding
performance in computer vision tasks such as biomedical imaging, including classification …

Denoising images corrupted with multiple types of noise is significantly challenging due to
their variable noise distribution. These numerous types of noise have a cumulative effect on …

This research aims to combine BiLSTM and CNN to provide a new model for applications in
image classification. A BiLSTM network is a long-term recurrent neural network (RNN) that …

This research aims to develop an image classification model by integrating long short-term
memory (LSTM) with a convolutional neural network (CNN). LSTM, which is a type of neural …

Image denoising is a fundamental challenge in the field of image processing, with the
primary goal of recovering high-quality images from noisy counterparts. This paper …