/ImageClassification_Project

Implementing simple NN, CNN and ResNet for image classification.

Primary LanguageJupyter Notebook

Image Classification

Table of Contents
  1. About The Project
  2. Phases
  3. Contact

About The Project

This project implements three types of networks with PyTorch and uses the cifar10 and MNIST Dataset for training and testing model.

Phases

Simple Neural Network

In this phase network is designed for MNIST dataset. Finall accuracy is 0.9682.
All further information about architecture of models and results are saved in the notebook.

Example Run

Convolutional Neural Network

In this phase network is designed for cifar10 dataset. Finall accuracy is 0.7462.
All further information about architecture of models and results are saved in the notebook.

Example Run

it does not work well :(

Example Run

ResNet

In this phase network is designed for cifar10 dataset. Finall accuracy is 0.9090.
All further information about architecture of models and results are saved in the notebook.

Example Run

Contact

Amirreza Naziri
Email: naziriamirreza@gmail.com

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