Developers: Lachanas Dimitris, Tilikidou Sofia, Zilachovinos Apostolos
This repository contains the implementation of the lab exercises for the course "Neural Networks in Computer Vision." The goal of this exercise is to utilize deep learning models for image classification, focusing on the creation, evaluation, and comparison of various neural network architectures, as well as the application of transfer learning.
Part 1: Comparing Neural Network Architectures Goal: Develop and compare a Deep Neural Network (DNN) and a Convolutional Neural Network (CNN) on the MNIST dataset.
Part 2: Transfer Learning Goal: Apply the best models from Question 1 to the fashion-MNIST dataset using transfer learning.