We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

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 ...

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) ...

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.

Discover how AI and Deep Learning are revolutionizing airport operations, from jet bridge autonomy to baggage classification, solving complex challenges with advanced technology. Many of us are ...

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet, the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 ...