a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results

This repository is dedicated to course notebooks and personal notes from my learning during the specialization.

[Frontiers in Comp. Neuro.] Deep Attention Super-Resolution of Brain Magnetic Resonance Images Acquired Under Clinical Protocols

This repository contains some comprehensive approaches for the purpose of classifying breast cancer tissue using whole slide images (WSIs).

Official Keras implementation for "On-Edge Deployment of Vision Transformers for Medical Diagnostics Using the Kvasir-Capsule Dataset."

This collection brings together the highest-signal research papers in modern AI from the invention of the Transformer to the frontier work of 2024–2025 into a single, curated map of the field

Participants in this Specialization have the opportunity to construct and train various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Transformers. They learn to enhance these networks with techniques such as Dropout, BatchNorm, Xavier/He initialization, among others.

A transformer-based arabic text summarizer trained on 160,000 Arabic Articles to extract key information and generate concise arabic summaries

• Prose Style Transfer - Final Project.

Pseudo-3D CNN networks in PyTorch.