Digit_Recognition_Web_App
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Published
20 hours ago •
maneprajakta
maneprajakta
A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.
Digit_Recognition_Web_App
link : https://maneprajakta.github.io/Digit_Recognition_Web_App/
Structure of App
keras - > Tensorflow.js ->(html + css + javascript)->github pages
Hello World of Object Recognition!
Aim:
To make a convolution neural network to recognise handwritten digits by training the model on MNIST dataset available in keras.
MNIST DATASET:
The training dataset contain 60000 images and testing contain 10000 images .Each image is 28x28 pixel and grey scale.
CNN MODEL OVERVIEW:
⚈ It is a 17 layer model with Conv2D,MaxPooling2D,BatchNormalization,Dense,Flatten and Dropout layer combination.
⚈ Input layer has 32 neuron and output layer has 10 neurons as 10 different clases exsist.
⚈ 30 epochs are used.
⚈ Categorical_loss is loss function and adam is used for optimization.
⚈ Model gives 99.15% accuracy.
For Deployment:
Save model using tensorflowjs converters as json file and weight as .h5 file.Use Tensorflow.js to load model and predict in javascript file
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maneprajakta
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A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.