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RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets...

Moved to https://github.com/rdiankov/openrave An open-source, cross-platform, plugin-based robot planning environment for autonomous robotics. Includes services like collision detection, physics, (inverse) kinematics, sensors, robot controls, python bindings, and a network scripting environment.

BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.

Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.