Age and Gender Estimation Using Convolutional Neural Network

Pre-trained VGG-Net Model for image classification using tensorflow

Modified version of U-net based on "Convolutional Networks for Biomedical Image Segmentation (Ronneberger et al., 2015)" paper.

Leveraging Transfer Learning on the classic CIFAR-10 dataset by using the weights from a pre-trained VGG-16 model.

Udacity Machine Learning Engineer Nanodegree Capstone Project : Dog breed classification using Convolutional Neural Networks

Neural Style Transfer Algorithm

Age-invariant face recognition based on deep features analysis

Bird Species Classification Using Transfer Learning

SFA : Small Faces Attention Face Detector, IEEE Access 2019

Covid-19 chest x_rays images multi-class classification while classes are (COVID, Pneumonia, normal)

Implementation of Neural Style Transfer algorithm with pre-trained VGG-16 Network & TensorFlow in Python 3.

A task from Udacity Deep Learning Nanodegree Program, with some basic CNN implementations for study purpose

brain tumor detection system using VGG16 architecture

Our system works on the detection of cataracts and type of classification on the basis of severity namely; mild, normal, and severe, in an attempt to reduce errors of manual detection of cataracts in the early ages using Machine Learning and Transfer Learning

fine tuning vgg16 and inception v3

Deep Learning Final Project

American Sign Language Classification Model

Predicting No of people present in the selected region using Spatial Divide and Conquer Network