Feed-forward neural network built from scratch trained to discriminate between hand-written digits. 28x28 pixel image samples from the MNIST dataset are used.
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Updated
Sep 28, 2016 - Java
Feed-forward neural network built from scratch trained to discriminate between hand-written digits. 28x28 pixel image samples from the MNIST dataset are used.
Red Neural que trabaje con MNIST
Run the TensorFlow MNIST model in Android application.
Based on tensorflow's handwritten digital Android project.
Code to convert the native MNIST data format to PNG images.
✏️ 1️⃣ | A simple handwritten digits recognition MLP. This project contains an android app as client and a python http server to make the recognition.
Deep neural network implemented in Java from scratch, without using library/framework.
Simple Reader for reading MNIST data files
MNIST with TensorFlow Lite on Android
A basic program that uses neural networks to classify MNIST handwritten digits.
Handwritten digits classification from MNIST with TensorFlow on Android; Featuring Tutorial!
Implementation of multi-layer perceptron neural network
A Neural Network Implementation in Java
Handwritten Feedforward Neural Net to Classify MNIST Digits
Running Keras CNN model on Android.
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