Arkiv Digital Sweden Data sets
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Updated
Sep 9, 2024 - HTML
Arkiv Digital Sweden Data sets
Collection of Machine Learning Algorithms
Figuring out which handwritten digits are most differentiated with PCA.
Interactive Handwritten Digit Recognition: An intuitive Keras and TensorFlow powered app with Streamlit UI. Draw and predict digits in real-time.
Handwritten digit classification web app using Streamlit
This code utilizes a neural network to classify handwritten digits (0-9) from the MNIST dataset. Explore the process of data preparation, model training, and evaluation for accurate digit recognition.
Handwritten Bangla Numeric Digits Classification using ResNet-34. The work uses a subset of the BanglaLekha-Isolated dataset. For details, read the README file.
This project offers a simple and intuitive interface for users to input text and generate images that showcase the text in a handwritten style. The generator supports several stylistic modifications including bold, underline, and color alterations, allowing users to create personalized and visually appealing images from their text.
Tensorflow implementation of Conditional GAN trained on MNIST dataset
Learns using the input from the testing_data how to compute the output
Handwritten Digit Recognition is the capacity of a computer to interpret the manually written digits from various sources like messages, bank cheques, papers, pictures etc
Python implementation of a Yatzy score sheet detection using OpenCV, TensorFlow, MNIST
A quick analysis of simple CNN architectures classifying Handwritten MNIST dataset.
A tutorial on image processing of handwritten digits.
Generation of Human-Like handwritten digits using different GAN Architectures. The models were developed using Low-Level Tensorflow.
Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI
Handwritten Digits and Alphabets Recognition using Convolutional Neural Networks
Recognition of handwritten digits using neural networks (From scratch)
A collection of 107,730 28x28 PNG files of digits from 0-9, with a dataset generator.
Classic MNIST Dataset Digital Image classifier with the use of DeeperConvolutional Neural Networks.
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