Python-based EOS smart-contract development & testing framework
- eos
- smart-contracts
- python
- unit-testing
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Python-based EOS smart-contract development & testing framework
Hardware testing for the software world. Real or virtual, local or remote, human, automated or agentic.
Deep and Machine Learning for Microscopy
[DEPRECATED] Self-Supervised Extrinsic Calibration using 3D Spatial Transformer Networks
Honeynet Project generic authenticated datafeed protocol
swiss army knife of Controller Area Networks (CAN) often used in cars and building automation, etc...
peartree: A library for converting transit data into a directed graph for sketch network analysis.
a network packet capture compiler
Botnet command & control monitor
Medical LLM agent and MRI segmentation workspace built on PharmaLLM, with LangGraph, vLLM, and BEU-Net.
TranslatedCaptcha recognition implemented with a convolutional neural network
Tools for working with GTFS public transit data in ArcGIS
Code that makes the Iowa Environmental Mesonet run, or run into the ground.
A micro neural network multilayer perceptron for MicroPython (used on ESP32 and Pycom modules)
The Algorand AlgoKit CLI is the one-stop shop tool for developers building on the Algorand network.
A simple, flexible, and extensible template for PyTorch. It's beautiful.
Malware Analysis Tool using Function Level Fuzzy Hashing
Shallow and Deep Convolutional Networks for Saliency Prediction
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
Watchtower | Self-hosted AI security assessment, asset intelligence, and evidence workflows.
Utility reporting system health and status via MQTT
Automation of some MAPT activities and interaction with the mobile Android device.
Research tooling for MW4 on-demand texture streaming: loopback proxy, hosts manager, resumable mirror, control GUI. Code and notes only - no game files.
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"