159 Open source projects that are alternatives of or similar to PaperSynth

Tensorflow-example：使用MNIST训练模型，并识别手写数字图片

CNN digit recognizer implemented in Keras Notebook, Kaggle/MNIST (0.995).

ichisadashioko.github.io/kanji-recognition/

A curated list of dedicated resources and applications

Controls and Visualization for AudioKit apps

Experiments on cluttered mnist dataset with Tensorflow.

Handwriting Recognition Web API Proposal

Implementation of LeNet5 without any auto-differentiate tools or deep learning frameworks. Accuracy of 98.6% is achieved on MNIST dataset.

Tensorflow implementation of adversarial auto-encoder for MNIST

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

Lingvo

(WIP) MIDI Sequencer Audio Unit

Convert hand written mathematical expressions and formula to Latext using Machine Learning

Implementation of a digit recognition using my Neural Network with the MNIST data set.

A realtime digit OCR on the browser using Machine Learning

手写数字识别。利用Tensorflow和MNIST实现的一个简单的手写数字识别程序。

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

Swift audio synthesis, processing, & analysis platform for iOS, macOS and tvOS

Handwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Recognize your own handwritten digits with Tensorflow, embedded in a PyQT5 GUI. The Neural Network was trained on MNIST.

A scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset

An efficient implementation of RNN-T Prefix Beam Search in C++/CUDA.

Tensorflow 2.0 implementation of Adversarial Autoencoders

Generative Adversarial Network for MNIST with tensorflow

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Kanji handwriting recognition for iOS using Zinnia.

Let's explore how we can extract text from forms

Playing with MNIST. Machine Learning. Generative Models.

GBDT (Gradient Boosted Decision Tree: 勾配ブースティング) のpythonによる実装

In-Browser Digit recognition with Tensorflow.js and React using Mnist dataset

MNIST classification using Multi-Layer Perceptron (MLP) with 2 hidden layers. Some weight-initializers and batch-normalization are implemented.

CNN classification model built in Keras used for Digit Recognizer task on Kaggle (https://www.kaggle.com/c/digit-recognizer)

A fast Tsetlin Machine implementation employing bit-wise operators, with MNIST demo.

Predict handwritten digits with CoreML

One-Shot Learning with Triplet CNNs in Pytorch

Creative Audio Programming with AudioKit and OpenFrameworks

TensorBasicModel

A small convolution neural network deep learning framework implemented in c++.

The simplest machine learning library for launching UIs, running evaluations, and comparing model performance.

Simple Implementation of many GAN models with PyTorch.

✏️ ☁️ iinkJS is the fastest way to integrate rich handwriting recognition features in your webapp.

Minimalist implementation of VQ-VAE in Pytorch

Non-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10

Çeşitli kütüphaneler kullanılarak Türkçe kod açıklamalarıyla TEMEL SEVİYEDE pratik derin öğrenme uygulamaları.

A simple iOS application that records audio and plays it back. (+some animations)

MNIST with TensorFlow Lite on Android

Generative Adversarial Networks in TensorFlow 2.0

Collection of generative models in Pytorch version.

Multi-Classification on dataset of MNIST

This program shows how Bounding-Box-Regression works in a visual form. Intersection over Union ( IOU ), Non Maximum Suppression ( NMS ), Object detection, 边框回归，边框回归可视化，交并比，非极大值抑制，目标检测。

Back Propagation, Python

Create adversarial images to fool a MNIST classifier in TensorFlow

🎨 An authorial collection of fundamental recipes on Creative Coding and Recreational Programming.

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

Keras MNIST for Handwriting Detection