Generalised deep learning model for semi-automated length measurement of fish in stereo-BRUVS

D Marrable, S Tippaya, K Barker, E Harvey… - Frontiers in Marine …, 2023 - frontiersin.org
Assessing the health of fish populations relies on determining the length of fish in sample
species subsets, in conjunction with other key ecosystem markers; thereby, inferring overall …

Transferable Deep Learning Model for the Identification of Fish Species for Various Fishing Grounds

T Hasegawa, K Kondo, H Senou - Journal of Marine Science and …, 2024 - mdpi.com
The digitization of catch information for the promotion of sustainable fisheries is gaining
momentum globally. However, the manual measurement of fundamental catch information …

[HTML][HTML] Towards a fully automated underwater census for fish assemblages in the Mediterranean Sea

K Bürgi, C Bouveyron, D Lingrand, B Dérijard… - Ecological …, 2024 - Elsevier
Assessing underwater biodiversity is labour-intensive and costly, but is crucial for measuring
the extent of the decline in local fish stock. In most cases, Underwater Visual Census (UVC) …

Marine video cloud: A cloud-based video analytics platform for collaborative marine research

Z Zheng, TS Ha, Y Chen, H Liang… - OCEANS 2023 …, 2023 - ieeexplore.ieee.org
With the increasing attention and corresponding developments of data collection of
underwater surveying/diving videos, a large number of underwater videos have been …

[HTML][HTML] Simultaneous, vision-based fish instance segmentation, species classification and size regression

P Climent-Perez, A Galán-Cuenca… - PeerJ Computer …, 2024 - peerj.com
Overexploitation of fisheries is a worldwide problem, which is leading to a large loss of
diversity, and affects human communities indirectly through the loss of traditional jobs …

[HTML][HTML] Estimating body weight of caged sea cucumbers (Apostichopus japonicus) using an underwater time-lapse camera and image analysis by semantic …

T Yoshida, K Suzuki, K Kogo - Smart Agricultural Technology, 2024 - Elsevier
Image analysis is being developed to improve the efficiency of fishery and aquaculture
technologies. Optical cameras are an easy and cost-effective method for monitoring fish and …

Robust Fish Recognition Using Foundation Models toward Automatic Fish Resource Management

T Hasegawa, D Nakano - Journal of Marine Science and Engineering, 2024 - mdpi.com
Resource management for fisheries plays a pivotal role in fostering a sustainable fisheries
industry. In Japan, resource surveys rely on manual measurements by staff, incurring high …

BiFormer Attention‐Guided Multiscale Fusion Mask2former Networks for Fish Abnormal Behavior Recognition and Segmentation

J Liu, Z Hu, Y Zhang, Y Li, J Yang… - Aquaculture Research, 2024 - Wiley Online Library
To address the issues of accurately identifying and tracking individual fish abnormal
behaviors and poor adaptability in the aquaculture field, this paper proposes a Mask2former …

Automatic fish size estimation from uncalibrated fish market images using computer vision and deep learning

P Climent-Pérez, A Galán-Cuenca… - … workshop on soft …, 2022 - Springer
Fisheries around the world show an overexploitation, which has led communities to find
management strategies to tackle the problem. However, strategies are often taken on the …

FishNet: Deep Neural Networks for Low-Cost Fish Stock Estimation

M Mots' oehli, A Nikolaev, WB IGede, J Lynham… - arXiv preprint arXiv …, 2024 - arxiv.org
Fish stock assessment often involves manual fish counting by taxonomy specialists, which is
both time-consuming and costly. We propose an automated computer vision system that …