Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Krupchytskyi: Deep learning networks are particularly good at analyzing large amounts of unstructured data, like images and text. It's widely used in chatbots, image recognition like that required for ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...

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 ...

• Leaf vein network geometry can predict levels of resource transport, defence and mechanical support that operate at different spatial scales. However, it is challenging to quantify network ...