Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

The new all-flash device combines workstation performance, on-device AI, and power independence to replace the laptop in professional field ...

A revolutionary new kind of computer is no longer science fiction — it’s alive. Australian biotech company Cortical Labs has ...

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

The increasing demand for sustainable materials has highlighted the importance of biocomposites; however, their computational analysis is challenging due to the high cost associated with traditional ...

Salient Object Detection in Optical Remote Sensing Images (ORSI-SOD) is vital for applications such as urban planning and disaster monitoring. Yet, existing deep models remain energy-intensive and ...

Reasoning and question answering, as fundamental cognitive functions in humans, remain significant hurdles for artificial intelligence. While large language models (LLMs) have achieved notable success ...