Semantic neural network to realize pixel-wise classification of 2D nano-material using Matlab

The repository implements the a simple Convolutional Neural Network (CNN) from scratch for image classification. I experimented with it on MNIST digits and COIL object dataset.

This is a Matlab implementation of a Convolution Neural network (CNN) that has been trained with the MNIST dataset to recognize handwritten numbers. Some of the functionality was implemented with the help of Yasutake Furukawa in the Computer Vision (CMPT412) class at SFU

Repository for the MATLAB code for the final project of Computer Vision and Pattern Recognition, a.y. 2021-2022. The project consists in a convnet multiclass classifier design and test.

Convolutional Neural Network (CNN) for building a numeric character recognition system trained on the MNIST dataset. (Written in Matlab) Spring 2021

A handwritten digit recognition system implemented using MATLAB, leveraging Convolutional Neural Networks (CNNs) for accurate classification. Processes and classifies digits from the MNIST dataset using convolutional layers for feature extraction, ReLU activation for non-linearity, and pooling layers for dimensionality reduction.

A VGG practical on convolutional neural networks