model-architecture

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)

CVPR 2025 (Highlight)

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.

MoLE (Mix-of-Language-Experts) model architecture for multilingual programming

This project utilizes transfer learning with the VGG16 model to perform classification tasks on a custom dataset. [AI Engineer]

This repo ModelCraft is an open-source of machine learning and deep learning architectures, from classical to advanced models. Each includes precise mathematical explanations and well-documented PyTorch code

Automated Tool for Hierarchical Exploration of Neural Architectures

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.

Building a network to predict steering angles from images

CNN model architecture implementations in Keras