Efficient Detection of Lesions During Endoscopy.

Endoscopy is a very important procedure in the medical field. It is used to detect almost any diseases associated with the gastrointestinal (GI) tract. Hence, the current work attempts to use Machine learning methods such that such medical procedures can be automated and used in real-time to ensure the proper diagnosis of patients. The current work implements the Tiny Darknet model with an attempt to efficiently classify the various medical conditions specified in the dataset used. Eventually, the Tiny Darknet succeeds in achieving a high classification speed, achieving up to a maximum speed of about 60 fps.