A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis A Saleh, IH Laradji, DA Konovalov, M Bradley, D Vazquez, M Sheaves Scientific Reports 10 (1), 14671, 2020 | 107 | 2020 |
Automatic weight estimation of harvested fish from images DA Konovalov, A Saleh, DB Efremova, JA Domingos, DR Jerry 2019 Digital image computing: Techniques and applications (DICTA), 1-7, 2019 | 72 | 2019 |
Computer vision and deep learning for fish classification in underwater habitats: A survey A Saleh, M Sheaves, M Rahimi Azghadi Fish and Fisheries 23 (4), 977-999, 2022 | 61 | 2022 |
Underwater fish detection with weak multi-domain supervision DA Konovalov, A Saleh, M Bradley, M Sankupellay, S Marini, M Sheaves 2019 international joint conference on neural networks (ijcnn), 1-8, 2019 | 58 | 2019 |
Estimating mass of harvested Asian seabass Lates calcarifer from images DA Konovalov World Journal of Engineering and Technology 6 (03), 15, 2018 | 35 | 2018 |
Weakly supervised underwater fish segmentation using affinity LCFCN IH Laradji, A Saleh, P Rodriguez, D Nowrouzezahrai, MR Azghadi, ... Scientific reports 11 (1), 1-10, 2021 | 30 | 2021 |
Applications of deep learning in fish habitat monitoring: A tutorial and survey A Saleh, M Sheaves, D Jerry, MR Azghadi Expert Systems with Applications, 121841, 2023 | 18 | 2023 |
Adaptive uncertainty distribution in deep learning for unsupervised underwater image enhancement A Saleh, M Sheaves, D Jerry, MR Azghadi arXiv preprint arXiv:2212.08983, 2022 | 17 | 2022 |
A deep learning localization method for measuring abdominal muscle dimensions in ultrasound images A Saleh, IH Laradji, C Lammie, D Vazquez, CA Flavell, MR Azghadi IEEE Journal of Biomedical and Health Informatics 25 (10), 3865-3873, 2021 | 14 | 2021 |
Affinity lcfcn: Learning to segment fish with weak supervision I Laradji, A Saleh, P Rodriguez, D Nowrouzezahrai, MR Azghadi, ... arXiv preprint arXiv:2011.03149, 2020 | 12 | 2020 |
Transformer-based self-supervised fish segmentation in underwater videos A Saleh, M Sheaves, D Jerry, MR Azghadi arXiv preprint arXiv:2206.05390, 2022 | 8 | 2022 |
A lightweight Transformer-based model for fish landmark detection A Saleh, D Jones, D Jerry, MR Azghadi arXiv preprint arXiv:2209.05777, 2022 | 5 | 2022 |
MFLD-net: a lightweight deep learning network for fish morphometry using landmark detection A Saleh, D Jones, D Jerry, MR Azghadi Aquatic Ecology 57 (4), 913-931, 2023 | 3 | 2023 |
Unsupervised fish trajectory tracking and segmentation A Saleh, M Sheaves, D Jerry, MR Azghadi arXiv preprint arXiv:2208.10662, 2022 | 3 | 2022 |
Prawn morphometrics and weight estimation from images using deep learning for landmark localization A Saleh, MM Hasan, HW Raadsma, MS Khatkar, DR Jerry, MR Azghadi Aquacultural Engineering 106, 102391, 2024 | 1 | 2024 |
Developing deep learning methods for aquaculture applications A Saleh James Cook University, 2020 | 1 | 2020 |
Semi-Supervised Weed Detection for Rapid Deployment and Enhanced Efficiency A Saleh, A Olsen, J Wood, B Philippa, MR Azghadi arXiv preprint arXiv:2405.07399, 2024 | | 2024 |
ShadowRemovalNet: Efficient Real-Time Shadow Removal A Saleh, A Olsen, J Wood, B Philippa, MR Azghadi arXiv preprint arXiv:2403.08142, 2024 | | 2024 |
How to track and segment fish without human annotations: a self-supervised deep learning approach A Saleh, M Sheaves, D Jerry, M Rahimi Azghadi Pattern Analysis and Applications 27 (1), 1-18, 2024 | | 2024 |
Precise Robotic Weed Spot-Spraying for Reduced Herbicide Usage and Improved Environmental Outcomes--A Real-World Case Study MR Azghadi, A Olsen, J Wood, A Saleh, B Calvert, T Granshaw, E Fillols, ... arXiv preprint arXiv:2401.13931, 2024 | | 2024 |