Digit recognition with Convolutional Neural Networks in WebGL
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Updated
Aug 17, 2016 - JavaScript
Digit recognition with Convolutional Neural Networks in WebGL
A scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset
A Machine Learning classifier for recognizing the digits for humans 🎰
RealTime DigitRecognition using Convolutional Neural Network(CNN) with keras.
Using OpenCV in python to recognize digits in a scanned page of handwritten digits.
Handwritten digit recognition using neural network trained on 60000 images from MNIST dataset
🔢 Computer will recognize the digits you wrote on a beautiful web-interface
Recognition of sequence of digits using tensorflow
All about Neural Networks!
CNN digit recognizer implemented in Keras Notebook, Kaggle/MNIST (0.995).
Recognize Digits using Deep Neural Networks in Google Chrome live!
Implementing CNN for Digit Recognition (MNIST and SVHN dataset) using PyTorch C++ API
Recognize handwritten multi-digit numbers using a CRNN model trained with synthetic data.
A handwritten digit recognition painter implementation on Basys 3 Artix-7 FPGA using Verilog.
A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.
This project offers an efficient method for identifying and recognizing handwritten text from images. Using a Convolutional Recurrent Neural Network (CRNN) for Optical Character Recognition (OCR), it effectively extracts text from images, aiding in the digitization of handwritten documents and automated text extraction.
This project demonstrates Handwritten digit recognition using Deep Learning
Attention mechanism with MNIST dataset
Recognize handwritten digits using back-propagation algorithm on MNIST data-set
Keras Fully Connected Neural Network using Python for Digit Recognition
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