AIMC Topic: Zooplankton
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Application of machine learning models for zooplankton abundance prediction in ponds of Southeastern Coastal Regions in Bangladesh.
Environmental monitoring and assessment
Jul 10, 2025
Zooplankton abundance prediction in surface water bodies is crucial because they reflect ecosystem health and have role in aquatic food webs and nutrient cycling. This study examined the applicability of machine learning algorithms to estimate zoopla...
Design of a fractional-order environmental toxin-plankton system in aquatic ecosystems: A novel machine predictive expedition with nonlinear autoregressive neuroarchitectures.
Water research
Apr 12, 2025
Artificial intelligence has transformed both plankton dynamics and hazardous material management under toxic environments by enhanced hazard prediction in detecting how toxins affect plankton population and potentially uncovering greater depth of eco...
An in situ digital synthesis strategy for the discovery and description of ocean life.
Science advances
Jan 17, 2024
Revolutionary advancements in underwater imaging, robotics, and genomic sequencing have reshaped marine exploration. We present and demonstrate an interdisciplinary approach that uses emerging quantitative imaging technologies, an innovative robotic ...
Deep-Learning-Based Automated Tracking and Counting of Living Plankton in Natural Aquatic Environments.
Environmental science & technology
May 19, 2023
Plankton are widely distributed in the aquatic environment and serve as an indicator of water quality. Monitoring the spatiotemporal variation in plankton is an efficient approach to forewarning environmental risks. However, conventional microscopy c...
Microplankton life histories revealed by holographic microscopy and deep learning.
eLife
Nov 1, 2022
The marine microbial food web plays a central role in the global carbon cycle. However, our mechanistic understanding of the ocean is biased toward its larger constituents, while rates and biomass fluxes in the microbial food web are mainly inferred ...
Hierarchical deep learning model to simulate phytoplankton at phylum/class and genus levels and zooplankton at the genus level.
Water research
Apr 23, 2022
Harmful algal blooms (HABs) have become a global issue, affecting public health and water industries in numerous countries. Because funds for monitoring HABs are limited, model development may be an alternative approach for understanding and managing...
Augmenting biologging with supervised machine learning to study behavior of the medusa .
The Journal of experimental biology
Aug 23, 2019
Zooplankton play critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood because of the difficulty in studying individuals Here, we combine biologging with supervised machine learning (ML) to propose a pipeline f...
Enhanced convolutional neural network for plankton identification and enumeration.
PloS one
Jul 10, 2019
Despite the rapid increase in the number and applications of plankton imaging systems in marine science, processing large numbers of images remains a major challenge due to large variations in image content and quality in different marine environment...
Microplastics do not increase toxicity of a hydrophobic organic chemical to marine plankton.
Marine pollution bulletin
Nov 17, 2018
Planktonic sea-urchin larvae actively ingest polyethylene microplastics (MP) that accumulate in the larval stomach and can be distinguished from natural food using polarized light microscopy. MP filtering rates were similar to those of natural partic...
Prognostication of zooplankton-driven cholera pathoepidemiological Dynamics: Novel Bayesian-regularized deep NARX neuroarchitecture.
Computers in biology and medicine
Jun 1, 2025
BACKGROUND: Cholera outbreaks pose significant health concerns, particularly through freshwater contamination through zooplankton serving as reservoirs for Vibrio Cholerae. Understanding these complex interactions within the aquatic ecosystem through...
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