Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision ...

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

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Image courtesy by QUE.com Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

The German sensor-maker Leuze claims that it has been able to cut measurement errors in demanding industrial applications by ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...