ModelHub.AI: Dissemination Platform for Deep Learning Models [article]

Ahmed Hosny, Michael Schwier, Christoph Berger, Evin P Örnek, Mehmet Turan, Phi V Tran, Leon Weninger, Fabian Isensee, Klaus H Maier-Hein, Richard McKinley, Michael T Lu, Udo Hoffmann (+4 others)
2019 arXiv   pre-print
Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among others. Additionally, the availability of open-source computational frameworks has lowered the barriers to implementing state-of-the-art methods across multiple domains. Albeit leading to major performance breakthroughs in some tasks, effective dissemination of deep learning algorithms remains challenging, inhibiting
more » ... eproducibility and benchmarking studies, impeding further validation, and ultimately hindering their effectiveness in the cumulative scientific progress. In developing a platform for sharing research outputs, we present ModelHub.AI (www.modelhub.ai), a community-driven container-based software engine and platform for the structured dissemination of deep learning models. For contributors, the engine controls data flow throughout the inference cycle, while the contributor-facing standard template exposes model-specific functions including inference, as well as pre- and post-processing. Python and RESTful Application programming interfaces (APIs) enable users to interact with models hosted on ModelHub.AI and allows both researchers and developers to utilize models out-of-the-box. ModelHub.AI is domain-, data-, and framework-agnostic, catering to different workflows and contributors' preferences.
arXiv:1911.13218v1 fatcat:4b4mdu4frzaozlgwaz6kvf4k7e