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

Image segmentation

SAM is a deep learning model (transformer based). When we give an image as input to the Segment Anything Model, it first passes through an image encoder and produces a one-time embedding for the entire image. The downsampling happens using 2D convolutional layers. Then the model concatenates it with the image embedding to get the final vector.

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

Development of a renal ultrasound computer aided tool using deep learning techniques.

Flood detector using effientnet as semantic segmentation model

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…

A PyTorch Implementation of Double-UNet

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.

Notebook for autosegmentation of Head and Neck CT images using CNN

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

Repo to host the UPC AIDL spring 2022 post-graduate project

Segmentation models with pretrained backbones for RSI semantic segmentation (Keras and TensorFlow Keras).

Computer vision and machine learning project to count and detect the ripeness of strawberries in images

Segmenting customers based on their behavior and preferences

PyTorch implementation of DoubleUNet for medical image segmentation