An Intuitive Desktop GUI Application For Recognizing Multiple Handwritten Digits Drawn At The Same Time. Trained On MNIST Dataset and Built With Python, OpenCV and TKinter
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Updated
Apr 7, 2021 - Python
An Intuitive Desktop GUI Application For Recognizing Multiple Handwritten Digits Drawn At The Same Time. Trained On MNIST Dataset and Built With Python, OpenCV and TKinter
Deep learning demos using MNIST data set with multiple neural network models
VAE Implementation with LSTM Encoder and CNN Decoder
A Convolutional neural network heavily based upon the tensorflow advanced MNIST example but equiped with labels to visualize and allowing the user to draw an image and then have the system predict the result.
Trained deep neural networks to predict and classify input image (MNISTDD) datasets with python.
Dockerize a Keras CNN model, which is wrapped in a Webapp using Flask Micro Framework
PyTorch implementation of a feed forward neural network to classify handwritten digits from the MNIST dataset
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