Implementation of Automated Annotation through Mask RCNN Object Detection model in CVAT using AWS EC2 Instance
Marielet Guillermo, Robert Kerwin C. Billones, Argel A. Bandala, Ryan Rhay P. Vicerra, Edwin Sybingco, Elmer P. Dadios, Alexis M. Fillone
Abstract
With machine learning-based innovations becoming a trend, practical resolutions of its implementation to large-scale data and computing problems must be able to cope up as well. Currently, Graphic Processing Units (GPUs) are being chosen over other available physical devices due to its powerful computing capability and easier handling. Several cloud service providers also made it possible for these to be accessible online allowing higher serviceability and lower cost upfront for businesses. With this said, the proponent would implement a common machine learning-based application, automated annotation through Mask RCNN Object Detection Model in CVAT, using AWS instance. The key purpose is to showcase the viability of deploying data and computing intensive system on the cloud.