The South African Weather Service (SAWS) has issued warnings for a severe cold front sweeping across the country this weekend ...

Neuromorphic computing, inspired by the human brain, offers a path to faster and more efficient AI. In a pioneering ...

Autoencoders are a type of artificial neural network utilized for unsupervised learning (Saha et al., 2019). These tools have been employed to detect potential patterns in biological data that may ...

Efforts are underway to transform mental health research/therapy, especially via the use of AI. I explore the latest via the ...

In this paper, we propose a novel regression model, Lightweight one-dimensional convolutional neural network (1D-CNN), for predicting nicotine content in tobacco leaves using one-dimensional (1D) NIR ...

Building on the principles of arbitrage pricing theory (APT), this study introduces a dynamic neural network model aimed at minimizing investment risk, optimizing portfolio allocation within ...

Understanding neural network dynamics is a cornerstone of systems neuroscience, bridging the gap between biological neural networks and artificial neural ...

Attackers inject malicious code into AI models hosted on the public repositories. These models allow attackers to manipulate ...

The study proposes a hybrid activation function based on the Artificial Neural Network algorithm. This function is used to classify the need for irrigation in various crops and predict the best time ...

This teaching package contains modular contents for the introduction of the fundamentals of Neural Networks. The package consists of a series of MATLAB Live Scripts with complementary PowerPoint ...

The model employs GA to maximize the probability of achieving the optimal configuration of an MLP neural network in an effort to estimate the ETo derived from the Penman-Monteith method (PM FAO-56).

Laboratory for Low Dimensional Materials, Institute of Physics, Bhubaneswar 751005, India ...