Purdue University's Robot Vision Lab seeks to uncover new knowledge to advance sensory intelligence for the machines of the future. Machine Learning has become an integral part of that process.

RVL strongly believes in collaborative research and open-source software development. Over the course of many years of research and software development for a variety of computer vision and artificial intelligence applications, we have gained many interesting insights and ideas as well as encountered a ton of technical-gotchas. We have often relied on the kindness of Samaritans who spend hours debugging code and then post their findings online to help other people avoid such pitfalls and save valuable time. We wish to use this platform in a similar fashion to share our findings/insights with the public domain to help other researchers and programmers.

For more information about RVL, visit our main website.

• Federated Learning with Openstack by Ankit Manerikar

• Mind your Cloud Carbon Footprint by Ankit Manerikar

• Using GPUs Resourcefully on the RVL Cloud by Ankit Manerikar

• Tools and Tricks for Building Efficient Neural Networks by Ankit Manerikar

• In Progress: Using Cloud Resources Optimally by Sonali Patil

• 17 December: Pixel to Geodesic coordinate transformations using GeoTIFFs and GDAL by Bharath Comandur
• 17 December: Lessons in OpenStack - Less is More by Bharath Comandur