Automatic Coral Detection using Neural Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959672" target="_blank" >RIV/49777513:23520/20:43959672 - isvavai.cz</a>

Result on the web

<a href="http://ceur-ws.org/Vol-2696/paper_63.pdf" target="_blank" >http://ceur-ws.org/Vol-2696/paper_63.pdf</a>

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Automatic Coral Detection using Neural Networks

Original language description

This paper presents methods that were utilized in the ImageCLEFcoral 2020 challenge. The challenge contains two following subtasks: automatic coral reef annotation and localization, and automatic coral reef image pixel-wise parsing. In the first subtask, we tested two methods - SSD, and Mask R-CNN. In the second subtask, we tested only Mask R-CNN. Performance improvements were achieved by careful cleaning of the dataset and by both offline and online data augmentations.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20205 - Automation and control systems

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

CLEF 2020 Working Notes

ISBN

—

ISSN

1613-0073

e-ISSN

—

Number of pages

7

Pages from-to

—

Publisher name

CEUR Workshop Proceedings

Place of publication

Thessaloniki

Event location

Thessaloniki, Greece

Event date

Sep 22, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—