AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Abstract: Deep learning methods have shown promising results in various hyperspectral image (HSI) analysis tasks. Despite these advancements, existing models still struggle to accurately identify fine ...

Abstract: Motion planning is a fundamental challenge in robotics, involving the creation of trajectories from start to goal states while meeting constraints like collision avoidance and joint limits.

RMSprop Optimizer Explained in Detail. RMSprop Optimizer is a technique that reduces the time taken to train a model in Deep Learning. The path of learning in mini-batch gradient descent is zig-zag, ...

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...

This is the official repository of the paper "TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling". It consists of two parts: One dot represents a performance score on one ...

From large language models to whole brain emulation, two rival visions are shaping the next era of artificial intelligence.

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction ...

Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new possibilities and reshaping industries. Despite its prevalence, ...