Developing and Evaluating Deep Learning Algorithms for Object Detection: Key Points for Achieving Superior Model Performance.

ABSTRACT: In recent years, artificial intelligence, especially object detection-based deep learning in computer vision, has made significant advancements, driven by the development of computing power and the widespread use of graphic processor units. Object detection-based deep learning techniques have been applied in various fields, including the medical imaging domain, where remarkable achievements have been reported in disease detection. However, the application of deep learning does not always guarantee satisfactory performance, and researchers have been employing trial-and-error to identify the factors contributing to performance degradation and enhance their models. Moreover, due to the black-box problem, the intermediate processes of a deep learning network cannot be comprehended by humans; a

SUBMITTER: Oh JH 

PROVIDER: S-EPMC10323413 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature