Two-phase instance segmentation for whiteleg shrimp larvae counting

Khai Thinh Nguyen, Chanh Nghiem Nguyen, Chien Yao Wang, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Whiteleg shrimp accounts for the highest proportion in the shrimp export of Vietnam. Yet, in hatcheries, shrimp larvae quantity is still estimated manually. Several approaches were proposed to address this issue but overlapping problem reduced accuracy significantly. In this paper, this problem is addressed by implementing two-phase Mask R-CNN based instance segmentation to segment shrimp larvae for counting purpose. Compared to one-phase Mask R-CNN, the accuracy of counting by applying two-phase Mask R-CNN increased by a maximum margin of 16.1%. Our model had remarkable results, with accuracy ranging from 92.2% to 95.4% for moderate overlapping images.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics, ICCE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728151861
DOIs
StatePublished - Jan 2020
Event2020 IEEE International Conference on Consumer Electronics, ICCE 2020 - Las Vegas, United States
Duration: 4 Jan 20206 Jan 2020

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume2020-January
ISSN (Print)0747-668X

Conference

Conference2020 IEEE International Conference on Consumer Electronics, ICCE 2020
Country/TerritoryUnited States
CityLas Vegas
Period4/01/206/01/20

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