Face detection using convolutional neural networks

Breast Cell Nuclei Segmentation, project work done as a part of Internship at Machine Vision Lab, IIT Roorkee.

Projet de segmentation de clientèle - Classification non supervisée

Code of Steel Defect Detection semantic segmentation.

Image segmentation

Project implementation of land cover classification problem. This repository contains the implementation of models in pytorch lightning and their results.

This is a complete Project that revolves around churn modeling and it contains every aspect from data cleaning down to model deployment. The data of a bank was used in this implementation. An Artificial Neural Network was trained and used to predict the probability that a given customer would leave the bank(With 87% Test accuracy) and for deploy…

The goal is to segment instances of microvascular structures, including capillaries, arterioles, and venules, to in automating the segmentation of microvasculature structures as it will improve researchers' understanding of how the blood vessels are arranged in human tissues.

Semantic segmentation models for self-driving cars. Models developed for "Lyft Udacity Challenge for Self-driving Cars".

Case Study- Segmentation

A deep learning image segmentation library and API on top of PyTorch.

It's Spread Through Air Spaces(STAS) competition in lung by using image segmentation STAS contours

Python script to remove background from a video, make use of google MediaPipe

This project is a Semantic Segmentation for Self Driving Cars made using Python. This project uses U-Net to segment the different regions of the image.

A Comprehensive Comparison of deep learning architectures for COVID-19 Image Classification and Segmentation

Using image segmentation to remove webcam background without using chromakey

Segmentation of lungs using 3D CT scan of the patient using 2D U-net procedure

Through segmentation analysis, we aim to uncover meaningful patterns within this data to better understand and target different customer segments. This could involve using techniques such as clustering algorithms like k-means or hierarchical clustering to group customers with similar attributes together.

General information for PyVinci. An application deployed for an extended hackathon competition hosted by the PyTorch Team.

This project aims to classify handwritten Kannada digits using multiple layers of algorithms.