MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop.

This implements training of popular model architectures, such as AlexNet, ResNet and VGG on the ImageNet dataset(Now we supported alexnet, vgg, resnet, squeezenet, densenet)

Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)

VGG16 Net implementation from PyTorch Examples scripts for ImageNet dataset

deeplearning.ai Tensorflow advance techniques specialization

CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders

ElasticModels is a elasticsearch object modeling tool designed to work in and asynchronous environment. Builded for official elasticsearch client library Main inspiration was mongoose project

Chest X-Ray Image classification using PyTorch.

This Repository contains TensorFlow implementation of different Image Segmentation Architecture on different types of datasets.

Official PyTorch and CVXPY implementation of Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming

Identify traffic sign images through Supervised Classification via Deep Learning and Computer Vision using Python, Tensorflow, Jupyter and Anaconda in AWS Cloud.

In this project I have designed a Traffic Sign Classifier, which classifies German Traffic Signs.

Deep Learning Project to Teach a Car to Drive Autonomously Using Only Camera Images.

Long Short-Term Memory (LSTM) network trained to classify emails as spam or non-spam. It processes email content to make accurate predictions and can be integrated into projects for efficient spam detection and email management.

Building a network to predict steering angles from images

CNN model architecture implementations in Keras

Research project on trafiic sign recognition using deep learning and computer vision.

Traffic signs classifier

This is my first personal project about training a deep learning algorithm for road traffic signs recognition.