Rainfall prediction is a critical task because many people rely on it, particularly in the
agricultural sector. Rainfall forecasting is difficult due to the ever-changing nature of weather …

The SARS-CoV-2 virus which originated in Wuhan, China has since spread throughout the
world and is affecting millions of people. When there is a novel virus outbreak, it is crucial to …

In this work, we propose two deep learning-based architectures tailored for gas identification
and quantification, which automatically tune hyper-parameters of the network for optimal …

Pneumonia is a bacterial, virus and fungi infection that attacks respiratory function. The
disease causes air sacs in the lungs inflamed and swollen. It conditions produce lungs filled …

In this paper, we proposed the modified deep learning method that combined Convolutional
Neural Network (CNN) and Kernel K-Means clustering for lung cancer diagnosis. The Anti …

We propose a practical Convolution Neural Network (CNN) model termed the CNN for
Semantic Segmentation for driver Assistance system (CSSA). It is a novel semantic …

Predictive models mapping double-stranded DNA to signals of regulatory activity should, in
principle, produce analogous (or “equivariant”) predictions whether the forward strand or its …

Spiking Neural Networks (SNNs) are energy-efficient artificial neural network models that
can carry out data-intensive applications. Energy consumption, latency, and memory …

3D shape recognition becomes necessary due to the popularity of 3D data resources. This
paper aims to introduce the new method, hybrid deep learning network convolution neural …

The first COVID-19 confirmed case was reported in Wuhan, China, and spread across the
globe with an unprecedented impact on humanity. Since this pandemic requires pervasive …