In this work, an automatic and reproducible methodology is proposed using computer vision techniques for sorting oranges by size and defects. Master thesis written in Spanish.

CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!

DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

A Matlab software package to do 2D cell segmentation.

Brain Tumor Image segmentation-Brats2019, 2020, 2021

A lightweight Franklin plugin for experimentation and segmentation.

cuCIM - RAPIDS GPU-accelerated image processing library

Hands-on Image processing using OpenCV

Segmentation of cancerous tumors using Mamba. Code, resources, and paper provided. We manage to make a small (42k param) model that can segment pretty well.

Cornerstone is a set of JavaScript libraries that can be used to build web-based medical imaging applications. It provides a framework to build radiology applications such as the OHIF Viewer.

Binarize, normalize, segment images and train models.

MTMAUNet: Multi-Task Multi-axis Attention UNet

Development of machine learning model for instance segmentation of nuclei cells for Kaggle Data Science Bowl 2018 challenge

Tools to work with the FlyWire connectome. Fully interoperable with navis.

collection of diffusion model papers categorized by their subareas

Customer-Segmentation---Purchasing-Behavior

Transforming 2D images into 3D semantically segmented scenes using innovative CNN architecture and COLMAP reconstruction.

Segmentation models with pretrained backbones. PyTorch.

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125