The repository contains the Jupyter Notebook that perform semantic segmentation using the famous U-Net. The encoder of the U-Net is replaced with the pretrained encoder.

A simple, easy-to-understand library for diffusion models using Flax and Jax. Includes detailed notebooks on DDPM, DDIM, and EDM with simplified mathematical explanations. Made as part of my journey for learning and experimenting with state-of-the-art generative AI.

Pure Unet to Denoise (with Notebook Tutorial)

This Repository contains TensorFlow implementation of different Image Segmentation Architecture on different types of datasets.

Repo of all deep learning models

Collection of notebooks for image segmentation tasks.

Wound healing analysis and segment the wound area

Deep learning architectures for semantic segmentation run on Jupyter Notebook: U-Net, MANet, MAResU-Net, MACU-Net.

[Imperial] Neural Network Model for Generation of Image Descriptors for Image Representation in the Euclidean Space.

In this repository you can find the jupyter notebooks used to take part at the competitions created for the Artifical Neural Networks and Deep Learning exam at Politecnico di Milano.

A tutorial that guides users through the process of fine-tuning a stable diffusion model using HuggingFace's diffusers library. The tutorial includes advice on suitable hardware requirements, data preparation using the BLIP Flowers Dataset and a Python notebook, and detailed instructions for fine-tuning the model.