Object Detection with Deep Learning for Underwater Environment

Chia Chin Wang, Hooman Samani, Chan Yun Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this research we have investigated the usage of deep learning algorithms for object detection in underwater environment and specifically we have employed YOLOv3 algorithm in our study. Details of the algorithm and experimental results are presented. We used available underwater database for training and investigated the method by experimenting to detect and identify the type of the fish in an aquarium in the lab. The results are also explained in this paper.

Original languageEnglish
Title of host publicationProceedings of 4th International Conference on Information Technology Research
Subtitle of host publicationBridging Digital Divide Through Multidisciplinary Research, ICITR 2019
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781728161990
DOIs
Publication statusPublished - 10 Dec 2019
Event4th International Conference on Information Technology Research, ICITR 2019 - Moratuwa, Sri Lanka
Duration: 10 Dec 201913 Dec 2019

Publication series

NameProceedings of 4th International Conference on Information Technology Research: Bridging Digital Divide Through Multidisciplinary Research, ICITR 2019

Conference

Conference4th International Conference on Information Technology Research, ICITR 2019
Country/TerritorySri Lanka
CityMoratuwa
Period10/12/1913/12/19

Keywords

  • Deep Learning
  • Object Detection
  • Underwater
  • YOLO

Fingerprint

Dive into the research topics of 'Object Detection with Deep Learning for Underwater Environment'. Together they form a unique fingerprint.

Cite this