The aim of this project is to implement an image classifier based on convolu- tional neural networks. Starting by implementing a simple shallow network and then refining it until a pre-trained ResNet18 is implemented, showing at each step how the accuracy of the model improves. The provided dataset (from [Lazebnik et al., 2006]) contains 15 cate…

Team Project for Data Analysis With Deep Learning class

Python OpenCV

Submission - Last Project : Image Classification - Machine Learning for Beginners - Machine Learning Path - DICODING

This project implements a Generative Adversarial Network (GAN) to generate fashion images from a Polyvore dataset. It explores GANs' ability to create realistic images for fashion recommendations, including data preparation, model design, training, and visualization. Potential applications include virtual try-ons and recommendations.

Image Augmentation

Deep Learning Final Project

Pistachios are nutritious nuts that are sorted based on the shape of their shell into two categories: Open mouth and Closed mouth. The open-mouth pistachios are higher in price, value, and demand than the closed-mouth pistachios. Because of these differences, it is considerable for production companies to precisely count the number of each kind.

This project is about how to apply image data augmentation in Keras. And focused on using the ImageDataGenerator class from Keras’ image preprocessing package, and gives insight of a variety of options available in this class for data augmentation and data normalization.

👤 Detect age and gender from facial images using deep learning with CNNs like VGG16 and ResNet, achieving high accuracy under various conditions.

Predefined pipelines for image augmentation

Image augmentation using pytorch and albumentations

Use convolutional neural networks (CNNs) to clone driving behavior and train a self-driving car to autonomously navigate a track.

Image Classification using Convolutional Neural Networks (CNN)!

Example application for training Google's pretrained Vision Transformer model on an image classification task with a large number of labels

Capstone Project for Udacity Machine Learning Nanodegree

A Traffic Sign Recognition Project which can help the driver recognise the signs via text as well as audio. Can be used at Night also.

implementation of two deep learning models—UNet and a custom-built CANet—for semantic segmentation of Indian traffic scenes. Using the India Driving Dataset, the goal is to accurately segment various traffic elements to facilitate applications in autonomous driving and smart traffic management.

Tumor detection using deep learning(Keras)