Age and Gender Estimation Using Convolutional Neural Network
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Updated
Oct 7, 2017 - Python
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
SFA : Small Faces Attention Face Detector, IEEE Access 2019
Bird Species Classification Using Transfer Learning
Implementation of Neural Style Transfer algorithm with pre-trained VGG-16 Network & TensorFlow in Python 3.
Covid-19 chest x_rays images multi-class classification while classes are (COVID, Pneumonia, normal)
A task from Udacity Deep Learning Nanodegree Program, with some basic CNN implementations for study purpose
brain tumor detection system using VGG16 architecture
fine tuning vgg16 and inception v3
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
Deep Learning Final Project
American Sign Language Classification Model
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