🧠 Enhance brain tumor diagnosis with automated 3D segmentation using U-Net and PyTorch, leveraging the BraTS 2020 dataset for precise analysis.

🧠 Automate 3D brain tumor segmentation using U-Net with PyTorch and MONAI, leveraging the BraTS 2020 dataset for precise clinical insights.

🔧 Enhance real-time effects processing with MirrorSynth, a robust Rust solution for streamlined development and improved productivity.

🎨 Transform grayscale images into color with this PyTorch U-Net model, trained on COCO for accurate image colorization and evaluation metrics.

🎧 Enhance MP3 audio quality by removing compression artifacts with a wavelet-based deep learning model for superior sound restoration.

(WIP) PyTorch/TensorFlow powered semantic segmentation software for cytological slides

🌐 Organize and showcase AI use cases, prompts, and workflows with this static site built on Eleventy, supporting multiple languages and themes.

🧠 Segment brain tumors accurately using a 2D U-Net model in PyTorch with the BraTS 2020 dataset for efficient evaluation and visualization.

🩺 Segment lungs from COVID-19 X-ray images using advanced deep learning techniques like U-Net and MobileNet-U-Net for improved accuracy and efficiency.

🎨 Generate images with integrated control signals using the mini-ControlNet model, built on UNet and trained on the CelebA dataset.

🐾 Implement a U-Net model for pet image segmentation, accurately classifying pets, backgrounds, and borders using the Oxford-IIIT Pet dataset.

🩺 Automate knee MRI segmentation using DiffuKnee’s diffusion model and U-Net pipeline for accurate and efficient multi-class results.

🧠 Implement U-Net in PyTorch for effective binary image segmentation, focusing on brain tumor detection with a complete pipeline from data prep to evaluation.

#1 Open Source Unity Networking Library

Clean one-file implementations of core diffusion ideas at increasing complexity - from ConvNet to Attention UNet with additions.

Easy to use high performance Network library for Unity 3d

A tool for cell instance aware segmentation in densely packed 3D volumetric images

A unified PyTorch framework for semantic segmentation of satellite imagery. Supports multi-spectral data, state-of-the-art architectures, and seamless large-scale inference for Earth Observation applications.

PyTorch-based multimodal brain tumor segmentation using BraTS 2020, featuring vanilla, residual, and attention-guided U-Net architectures with comprehensive W&B experiment tracking.