This repository contains the implementation of famous ResNet50 which is state of art technique for image classification

Implementation of Yolo v3 object detection fully convolutional neural network model in Tensorflow & Keras

Segmentation pipeline that uses a U-Net backbone to perform segmentation on the Cityscapes dataset. Conducted experiments to analyse the impact of the skip connections of the U-Net on the quality of the segmentation masks. These masks are also qualitatively analysed using the Intersection-over-Union (IoU) metric

Model Pipelines for GNNs, VAEs, Neural Style Transfer, and other kinds of models!

PyTorch Implementation of Hybrid Skip Connection for UNet

road and traffic segmentation with IoU metric and DICE coffecient

Refer Readme.md

RoboND Term 1 Deep Learning Project, Follow-Me

Code accompanying the paper: "Hybrid Skip: A Biologically Inspired Skip Connection for the UNet Architecture"

Replication of Jasper speech-to-text network using Intel optimized TensorFlow.

The main goal of this project is to come up with an architecture having the highest test accuracy on the CIFAR-10 image classification dataset, under the constraint that model has no more than 5 million parameters.

IEEE paper implementation of Single-View 2D-3D Reconstruction.

This project demonstrates the implementation of ResNet50 from scratch and its application for chest cancer classification using the Chest CT-scan Images dataset.

Reconstructing Medical Images using Generative model.

This is the official implementation of "Novel View Synthesis with Skip Connections" (ICIP 2020)

Implementations of different variations of U-net - adding deconv layers, dense net variant and including skip connections

Graduation Project. Applying Generative Adversarial Networks(GAN) with Residual-In-Residual(RIR) blocks.

ResNet-34 Model trained from scratch to classify 450 different species of birds with 98.6% accuracy.

The project presents a comparative study of Brain Tumor Segmentation using 3 approaches - 1) Sobel Operator and U-Net, 2) V-Net, 3) W-Net