Abstract Hand Gesture Recognition (HGR) is a challenging computer vision task. Recently,
by taking advantages of deep learning-based models, HGR methods have achieved …

Atherosclerosis, a chronic inflammatory disease affecting the large arteries, presents a
global health risk. Accurate analysis of diagnostic images, like computed tomographic …

Sign languages play a crucial role in enabling differently-abled people to communicate and
express their feelings. The advent of newer technologies in machine learning and sensors …

The use of back propagation through the time learning rule enabled the supervised training
of deep spiking neural networks to process temporal neuromorphic data. However, their …

This paper explores the synergistic potential of neuromorphic and edge computing to create
a versatile machine learning (ML) system tailored for processing data captured by dynamic …

As the technology industry is moving towards implementing tasks such as natural language
processing, path planning, image classification, and more on smaller edge computing …

Pathological alterations in the human vascular system underlie many chronic diseases, such
as atherosclerosis and aneurysms. However, manually analyzing diagnostic images of the …

For human–computer interaction, one of the most important tools is Sign Language
Recognition in which one of the significant research topics is static Hand Gesture (HG) and …

Facial expression recognition is a popular and challenging area of research in machine
learning applications. Facial expressions are critical to human communication and allow us …

Recent years have witnessed the deep involvement of hand gesture recognition in Internet
of Things (IoT) devices in healthcare, autonomous driving, virtual reality, augmented reality …