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Harmful Algal and Cyanobacterial Blooms (HABs), occurring in inland and maritime waters, pose threats to natural environments by producing toxins that affect human and animal health. In the past, HABs have been assessed mainly by the manual…

Systems and Control · Electrical Eng. & Systems 2023-09-12 José L. Risco-Martín , Segundo Esteban , Jesús Chacón , Gonzalo Carazo-Barbero , Eva Besada-Portas , José A. López-Orozco

A disconcerting ramification of water pollution caused by burgeoning populations, rapid industrialization and modernization of agriculture, has been the exponential increase in the incidence of algal growth across the globe. Harmful algal…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Arabinda Samantaray , Baijian Yang , J. Eric Dietz , Byung-Cheol Min

This paper describes the application of machine learning techniques to develop a state-of-the-art detection and prediction system for spatiotemporal events found within remote sensing data; specifically, Harmful Algal Bloom events (HABs).…

Machine Learning · Computer Science 2020-04-17 P. R. Hill , A. Kumar , M. Temimi , D. R. Bull

We present a self-supervised machine learning framework for detecting and mapping the severity and speciation of harmful algal blooms (HABs) using multi-sensor satellite data. By fusing reflectance data from operational polar-orbiting…

Machine Learning · Computer Science 2026-02-03 Nicholas LaHaye , Kelly M. Luis , Michelle M. Gierach

Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filter feeders, they can accumulate high concentrations of marine…

Cyanobacterial Harmful Algal Blooms (CyanoHABs) pose significant threats to aquatic ecosystems and public health globally. Lake Champlain is particularly vulnerable to recurring CyanoHAB events, especially in its northern segment:…

Climate change is increasing the frequency and severity of harmful algal blooms (HABs), which cause significant fish deaths in aquaculture farms. This contributes to ocean pollution and greenhouse gas (GHG) emissions since dead fish are…

Computer Vision and Pattern Recognition · Computer Science 2022-08-05 Nitpreet Bamra , Vikram Voleti , Alexander Wong , Jason Deglint

Harmful algal blooms (HABs) can threaten coastal infrastructure, fisheries, and desalination dependent water supplies. This project (REDNET-ML) develops a reproducible machine learning pipeline for HAB risk detection along the Omani…

Machine Learning · Computer Science 2026-03-05 Ameer Alhashemi

Harmful algal blooms are a growing threat to inland water quality and public health worldwide, creating an urgent need for efficient, accurate, and cost-effective detection methods. This research introduces a high-performing methodology…

Machine Learning · Computer Science 2025-12-05 Ioannis Nasios

Several theories have been proposed to explain the development of harmful algal blooms (HABs) produced by the toxic dinoflagellate \emph{Karenia brevis} on the West Florida Shelf. However, because the early stages of HAB development are…

Atmospheric and Oceanic Physics · Physics 2009-11-13 M. J. Olascoaga , F. J. Beron-Vera , L. E. Brand , H. Koçak

Harmful algae blooms (HABs), which produce lethal toxins, are a growing global concern since they negatively affect the quality of drinking water and have major negative impact on wildlife, the fishing industry, as well as tourism and…

Computer Vision and Pattern Recognition · Computer Science 2018-05-04 Jason L. Deglint , Chao Jin , Angela Chao , Alexander Wong

Diarrhetic Shellfish Poisoning (DSP) is a global health threat arising from shellfish contaminated with toxins produced by dinoflagellates. The condition, with its widespread incidence, high morbidity rate, and persistent shellfish…

Under the impact of global climate changes and human activities, harmful algae blooms in surface waters have become a growing concern due to negative impacts on water related industries. Therefore, reliable and cost effective methods of…

Computer Vision and Pattern Recognition · Computer Science 2018-10-26 Jason L. Deglint , Chao Jin , Alexander Wong

We introduce a unique semantic segmentation dataset of 6,096 high-resolution aerial images capturing indigenous and invasive grass species in Bega Valley, New South Wales, Australia, designed to address the underrepresented domain of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Sophia J. Abraham , Jin Huang , Brandon RichardWebster , Michael Milford , Jonathan D. Hauenstein , Walter Scheirer

Cyanobacteria are the most frequent dominant species of algal blooms in inland waters, threatening ecosystem function and water quality, especially when toxin-producing strains predominate. Enhanced by anthropogenic activities and global…

Quantitative Methods · Quantitative Biology 2024-10-14 Claudia Fournier , Raul Fernandez-Fernandez , Samuel Cirés , José A. López-Orozco , Eva Besada-Portas , Antonio Quesada

As a social being, we have an intimate bond with the environment. A plethora of things in human life, such as lifestyle, health, and food are dependent on the environment and agriculture. It comes under our responsibility to support the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Semanto Mondal

This paper investigates using satellite data to improve adaptive sampling missions, particularly for front tracking scenarios such as with algal blooms. Our proposed solution to find and track algal bloom fronts uses an Autonomous…

Systems and Control · Electrical Eng. & Systems 2023-05-02 Joana Fonseca , Sriharsha Bhat , Matthew Lock , Ivan Stenius , Karl H. Johansson

Water quality has a direct impact on industry, agriculture, and public health. Algae species are common indicators of water quality. It is because algal communities are sensitive to changes in their habitats, giving valuable knowledge on…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Peisheng Qian , Ziyuan Zhao , Haobing Liu , Yingcai Wang , Yu Peng , Sheng Hu , Jing Zhang , Yue Deng , Zeng Zeng

Marine microalgae are widespread in the ocean and play a crucial role in the ecosystem. Automatic identification and location of marine microalgae in microscopy images would help establish marine ecological environment monitoring and water…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Shizheng Zhou , Juntao Jiang , Xiaohan Hong , Yan Hong , Pengcheng Fu

Cyanobacterial blooms (CBs) pose significant global challenges due to their harmful toxins and socio-economic impacts, with nutrient availability playing a key role in their growth, as described by ecological stoichiometry (ES). However,…

Analysis of PDEs · Mathematics 2025-02-19 Jacob Serpico , Kyunghan Choi , B. A. Zambrano-Luna , Tianxu Wang , Hao Wang
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