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A Self-learning Approach for Beggiatoa Coverage Estimation in Aquaculture
Citation
Chen, Y and Zhou, Y and Tran, S and Park, M and Hadley, S and Lacharite, M and Bai, Q, A Self-learning Approach for Beggiatoa Coverage Estimation in Aquaculture, Lecture Notes in Artificial Intelligence 13151, 02-04 February 2022, Sydney, pp. 405-416. ISSN 0302-9743 (2022) [Refereed Conference Paper]
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DOI: doi:10.1007/978-3-030-97546-3_33
Abstract
Beggiatoa is a bacterium that is associated with anoxic conditions
beneath salmon aquaculture pens. Assessing the percentage coverage
on the seafloor from images taken beneath a site is often undertaken as
part of the environmental monitoring process. Images are assessed manually
by observers with experience in identifying Beggiatoa. This is a time-consuming
process and results can vary significantly between observers.
Manually labelling images in order to apply visual learning techniques is
also time-consuming and expensive as deep learning relies on very large
data sets for training. Image segmentation techniques can automatically
annotate images to release human resources and improve assessment efficiency.
This paper introduces a combination method using Otsu thresholding
and Fully Convolutional Networks (FCN). The self-learning method
can be used to estimate coverage and generate training and testing data
set for deep learning algorithms. Results showed that this combination of
methods had better performance than individual methods.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | artificial intelligence, aquaculture, Beggiatoa, self-learning |
| Research Division: | Information and Computing Sciences |
| Research Group: | Artificial intelligence |
| Research Field: | Artificial life and complex adaptive systems |
| Objective Division: | Environmental Management |
| Objective Group: | Coastal and estuarine systems and management |
| Objective Field: | Assessment and management of coastal and estuarine ecosystems |
| UTAS Author: | Chen, Y (Miss Yanyu Chen) |
| UTAS Author: | Zhou, Y (Miss Yunjue Zhou) |
| UTAS Author: | Tran, S (Dr Son Tran) |
| UTAS Author: | Park, M (Dr Mira Park) |
| UTAS Author: | Hadley, S (Mr Scott Hadley) |
| UTAS Author: | Lacharite, M (Dr Myriam Lacharite) |
| UTAS Author: | Bai, Q (Dr Quan Bai) |
| ID Code: | 154916 |
| Year Published: | 2022 |
| Deposited By: | Sustainable Marine Research Collaboration |
| Deposited On: | 2023-01-18 |
| Last Modified: | 2023-01-18 |
| Downloads: | 0 |
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