In modern‐day medicine, medical imaging has undergone immense advancements and can
capture several biomedical images from patients. In the wake of this, to assist medical …

The evolution of low-cost embedded systems is growing exponentially; likewise, their use in
robotics applications aims to achieve critical task execution by implementing sophisticated …

A simplified hyperchaotic canonical Chua's oscillator (referred as SHCCO hereafter) made
of only seven terms and one nonlinear function of type hyperbolic sine is analyzed. The …

The role of preprocessing and segmentation are vital in image processing and computer
vision. The medical images are prone to noise and the filtering algorithms are used for noise …

Abstract Background and objectives Deep Learning (DL) and Machine Learning (ML) have
brought several breakthroughs to biomedical image analysis by making available more …

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

With the passage of time, the importance of spatio-temporal data (STD) is increasing day by
day, but the spatiotemporal characteristics of STD bring huge challenges to data processing …

This study explores the efficacy of employing the Fractional Wavelet Filter (FrWF) as a photo
compression technique optimized for low-resource platforms, specifically targeting the …

This article is investigating from one of best control technique known as periodically
intermittent discrete observation control (PIDOC), the problem of global synchronization …

Deep learning and machine learning provide more consistent tools and powerful functions
for recognition, classification, reconstruction, noise reduction, quantification and …