AI is a broad concept, grou** initiatives that use a computer to perform tasks that would
usually require a human to complete. AI methods are well suited to predict clinical outcomes …

The recent advancements in the surging field of Deep Learning (DL) have revolutionized
every sphere of life, and the healthcare domain is no exception. The enormous success of …

Deep neural networks (DNNs) have become a relevant subject in the classification of radio
frequency signals and remote sensing data. A primary challenge is a tradeoff between …

The self-powered fault diagnosis methods provide a new idea to realize fault diagnosis
without using wired sensors or battery-supported sensors. However, current self-powered …

Simple Summary One of the hottest areas in deep learning is computerized tumor diagnosis
and treatment. The identification of tumor markers, the outline of tumor growth activity, and …

Most proteins exert their functions by interacting with other proteins, making the identification
of protein-protein interactions (PPI) crucial for understanding biological activities …

In this paper, we design a technologically intelligent wheelchair with eye-movement control
for patients with ALS in a natural environment. The system consists of an electric wheelchair …

On the remote sensing images of marine synthetic aperture radar (SAR), ship targets often
occupy only a small part of an image, and the rest are all sea and coastal backgrounds …

This work presents a system, where deep learning was used on images captured with a
digital camera to simultaneously determine the API concentration and the particle size …

Traditional methods for identifying gear faults typically require a substantial number of faulty
samples, which in reality are challenging to obtain. To tackle this challenge, this paper …