Search Results for author: Alzayat Saleh

Found 14 papers, 3 papers with code

ShadowRemovalNet: Efficient Real-Time Shadow Removal

no code implementations13 Mar 2024 Alzayat Saleh, Alex Olsen, Jake Wood, Bronson Philippa, Mostafa Rahimi Azghadi

We propose ShadowRemovalNet, a novel method designed for real-time image processing on resource-constrained hardware.

Edge-computing Shadow Removal

Prawn Morphometrics and Weight Estimation from Images using Deep Learning for Landmark Localization

no code implementations15 Jul 2023 Alzayat Saleh, Md Mehedi Hasan, Herman W Raadsma, Mehar S Khatkar, Dean R Jerry, Mostafa Rahimi Azghadi

In this study, we applied a novel DL approach to automate weight estimation and morphometric analysis using the black tiger prawn (Penaeus monodon) as a model crustacean.

Adaptive Uncertainty Distribution in Deep Learning for Unsupervised Underwater Image Enhancement

1 code implementation18 Dec 2022 Alzayat Saleh, Marcus Sheaves, Dean Jerry, Mostafa Rahimi Azghadi

This makes it difficult to train supervised deep learning models on large and diverse datasets, which can limit the model's performance.

Image Enhancement

A lightweight Transformer-based model for fish landmark detection

no code implementations13 Sep 2022 Alzayat Saleh, David Jones, Dean Jerry, Mostafa Rahimi Azghadi

Transformer-based models, such as the Vision Transformer (ViT), can outperform onvolutional Neural Networks (CNNs) in some vision tasks when there is sufficient training data.

Inductive Bias

Applications of Deep Learning in Fish Habitat Monitoring: A Tutorial and Survey

no code implementations11 Jun 2022 Alzayat Saleh, Marcus Sheaves, Dean Jerry, Mostafa Rahimi Azghadi

This paper is written to serve as a tutorial for marine scientists who would like to grasp a high-level understanding of DL, develop it for their applications by following our step-by-step tutorial, and see how it is evolving to facilitate their research efforts.

Transformer-based Self-Supervised Fish Segmentation in Underwater Videos

no code implementations11 Jun 2022 Alzayat Saleh, Marcus Sheaves, Dean Jerry, Mostafa Rahimi Azghadi

Our proposed model is trained on videos -- without any annotations -- to perform fish segmentation in underwater videos taken in situ in the wild.

Representation Learning Segmentation +1

Computer Vision and Deep Learning for Fish Classification in Underwater Habitats: A Survey

no code implementations14 Mar 2022 Alzayat Saleh, Marcus Sheaves, Mostafa Rahimi Azghadi

This information is essential for developing sustainable fisheries for human consumption, and for preserving the environment.

A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images

no code implementations30 Sep 2021 Alzayat Saleh, Issam H. Laradji, Corey Lammie, David Vazquez, Carol A Flavell, Mostafa Rahimi Azghadi

US images can be used to measure abdominal muscles dimensions for the diagnosis and creation of customized treatment plans for patients with Low Back Pain (LBP), however, they are difficult to interpret.

Affinity LCFCN: Learning to Segment Fish with Weak Supervision

1 code implementation6 Nov 2020 Issam Laradji, Alzayat Saleh, Pau Rodriguez, Derek Nowrouzezahrai, Mostafa Rahimi Azghadi, David Vazquez

Leading automatic approaches rely on fully-supervised segmentation models to acquire these measurements but these require collecting per-pixel labels -- also time consuming and laborious: i. e., it can take up to two minutes per fish to generate accurate segmentation labels, almost always requiring at least some manual intervention.

Segmentation

A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis

1 code implementation28 Aug 2020 Alzayat Saleh, Issam H. Laradji, Dmitry A. Konovalov, Michael Bradley, David Vazquez, Marcus Sheaves

The dataset consists of approximately 40 thousand images collected underwater from 20 \green{habitats in the} marine-environments of tropical Australia.

Automatic Weight Estimation of Harvested Fish from Images

no code implementations6 Sep 2019 Dmitry A. Konovalov, Alzayat Saleh, Dina B. Efremova, Jose A. Domingos, Dean R. Jerry

The two CNNs were applied to the rest of the images and yielded automatically segmented masks.

Underwater Fish Detection with Weak Multi-Domain Supervision

no code implementations26 May 2019 Dmitry A. Konovalov, Alzayat Saleh, Michael Bradley, Mangalam Sankupellay, Simone Marini, Marcus Sheaves

Given a sufficiently large training dataset, it is relatively easy to train a modern convolution neural network (CNN) as a required image classifier.

Fish Detection General Classification

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