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alzayats/README.md

Alzayat Saleh

Deep Learning · Computer Vision · Marine Science

About Me

I'm a Postdoctoral Research Fellow at AIMS@JCU (Australian Institute of Marine Science / James Cook University) based in Townsville, North Queensland. My work sits at the intersection of deep learning, computer vision, and marine science -- building AI systems that help us understand and monitor ocean ecosystems at scale.

  • Creator of the DeepFish dataset -- a benchmark for underwater fish analysis
  • Building tools for automated reef monitoring, fish measurement, and underwater image quality assessment
  • Focused on making deep learning practical for ecological research
  • Full publication list and research portfolio at alzayats.github.io

Scholar Stats

1,415
Citations		 16
h-index		 20
i10-index		 42
Publications

Last updated: November 09, 2026 via Google Scholar | View full profile

Featured Projects

DeepFish


A large-scale benchmark dataset for underwater fish analysis -- supporting classification, localization, counting, and segmentation tasks. Widely adopted in marine AI research.

UDnet


Adaptive Uncertainty Distribution in Deep Learning for Unsupervised Underwater Image Enhancement. A novel approach to improving degraded underwater imagery.

Research Domains

Coral Reef Monitoring        ──  Large-scale underwater image stitching & LTMP analysis
AutoFish Vision Pro          ──  AI-powered non-invasive fish measurement for aquaculture
Underwater Image Quality     ──  Automated IQA for marine monitoring pipelines
Habitat Mapping              ──  Deep learning for benthic and geomorphic classification

Tech Stack

GitHub Stats

Open to collaborations in AI, marine robotics, and agricultural tech.
Get in touch · View publications

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  1. DeepFish DeepFish Public

    JCU DeepFish dataset

    Python 140 31

  2. UDnet UDnet Public

    Adaptive Uncertainty Distribution in Deep Learning for Unsupervised Underwater Image Enhancement

    Python 71 7

  3. cross-habitat-marine cross-habitat-marine Public

    Benchmark and code for measuring how many labelled images are needed to deploy automated image recognition at a new marine monitoring site. Vision foundation models and CNNs compared across five da…

    Python

  4. pinn-reef-thermal pinn-reef-thermal Public

    Physics-informed neural network for reconstructing depth-resolved coral reef thermal fields from NOAA Coral Reef Watch satellite SST and sparse in-situ AIMS loggers.

    Python 1

  5. MHaghighat98/WeedVG-gRefCW MHaghighat98/WeedVG-gRefCW Public

    Crop and Weed Instance-level Generalised Visual Grounding - ECCV 2026

    Python 2

  6. open-AIMS/UNIQAT open-AIMS/UNIQAT Public

    Underwater Image Quality Assesment Toolkit

    Python 2

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