Theses

Deep Autoencoder Approach to Enhance Low-Light Images during Minimally Invasive Procedures

Undergraduate Final Work, 2019

This project presents a model based on a deep neural approach that is able to improve low-light surgical images, making them more optimized for analysis processes performed by human surgeons or assistant robots.

Advisor: Antonio Carlos dos Santos Souza.

Recommended citation: Carvalho, Caio Jordão; Souza, Antonio Carlos. (2019). "Deep Autoencoder Approach to Enhance Low-Light Images during Minimally Invasive Procedures." Download.