Datasets used in the NLSAM paper
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Updated
Feb 12, 2017 - Brainfuck
Datasets used in the NLSAM paper
These functions will randomly distort image data to amplify total amount of images for use in machine learning algorithms.
This is a simple project to generate simple cropped images with characters. You can generate with Chinese or English characters. Backgrounds are also allowed. Medical bills simulation are also included.
App for synthetically generating new images from a set of images. Primary use case is in helping train convolutional neural networks.
Synthetic Minority Over-sampling Technique Implementation
A command line tool used to create synthetic network profiles and synthetic hosts in JSON.
Basic GANs with variety of loss functions as an exercise for my Thesis with Prof. Randy Paffenroth. KL, Reverse-KL, JS and Wasserstein GAN.
The repository provides a synthetic multivariate time series data generator. The implementation is an extention of the cylinder-bell-funnel time series data generator. The scipt enables synthetic data generation of different length, dimensions and samples.
Code for creating the flying furniture dataset. Used for The Flying Furniture Challenge, an in-class kaggle competition.
Using synthetic data in combination with Deep Learning, to determine if a system can be made that will be able to recognise and classify correctly real traffic signs.
Privacy & Security Lab
Object detection and classification
Make Gapminder-style synthetic datasets
Semantic Segmentation using Resource Efficient Deep Learning
R package for Cardiovascular Risk Dataset and Data generation script
A generator for synthetic, multivariate & heterogeneous datasteams with probabilistically repeating patterns.
Generates synthetic data to apply simulations for causal inference
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