Classificador MNIST
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Updated
Jan 25, 2020 - MATLAB
Classificador MNIST
Uses vanilla backpropagation to train a basic multi-layer network to classify digits
A Machine Learning project that uses EM and Bernoulli mixes to classify digits
Verification of a VAE and SegNet using NNV
Temele la Metode Numerice
This is a basic project aimed at recognizing hand-written digits using Matlab.
Just another BP simulation.
A simple neural network implementation for MNIST dataset
A Neural Network from scratch (Extreme Learning Machine), trained on MNIST (97% accuracy).
This project contains example of Matlab interface for Caffe (known as Matcaffe). Currently, the example includes
Recognise Handwritten Digits MNIST data set using Neural Networks and Multi class Classification for Logisitc Regression
This repository encloses the programmatic part of the research into equivalence of Hebbian learning and the SVN formalism, exploring hypothesis brought forward in [On the equivalence of Hebbian learning and the SVM formalism [Nowotny, T and Huerta, R]
Test my MNIST data using kNN
Hand-written digit recognition on MNIST dataset
UB Computer Vision
Recognizing hand-written digits with an accuracy of 97.52%
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