This project utilizes Generative Adversarial Networks (GANs) to tackle the problem of credit card fraud detection. GANs are a powerful deep learning technique that can be used for generating synthetic data, which can be beneficial in situations with imbalanced datasets, such as fraud detection.

JR (jrnd.io) Source Connector for Apache Kafka Connect

A tool to generate synthetic dataset of corporate travels

An add-on for Blender that allows you to generate and render three-dimensional scenes that can be automatically annotated and used for training neural networks.

A toolbox to generate synthetic datasets of rotating 2D or 3D shapes.

Implementation of BISECT from [2] for Hidden Outlier generation.

Generates structured synthetic datasets using Pydantic v2 for validation and Azure OpenAI for generating realistic open string data. It supports configurable data schemas, distributions, dependencies, and prompts.

[DEMO] "Pose Estimation in Gebäuden anhand von Convolutional Neural Networks und simulierten 3D-Daten" as an example of PDF-generation via LaTeX - good old days 2019, supervised by Prof. Dr.-Ing. Markus Könug & M. Sc. Patrick Herbers | click here

Synthetic Credit Card Transaction Generator used in the Sparkov program.

Project C

Code to generate skin cancer syntetic images

A toolkit for generating synthetic datasets for 6DOF object pose estimation

A Python-based project that uses object-oriented programming to analyze synthetic stock market data. It explores index performance, volatility trends, market classifications, and generates insightful visualizations to support financial decision-making.

Explore techniques for imbalanced classification with Python. Compare oversampling, undersampling, and ensemble methods using scikit-learn and imbalanced-learn. 🐙📊

SensibleSleep is an open-source Python package that implements a Hierarchical Bayesian model for learning sleep patterns from smartphone screen-on events.

Evaluating the Potential of Generative Techniques to Improve Generalization in Federated Learning

Script for generate randomly a dataset containing simple shapes for asserting video frame interpolation generative models