AIMC Topic: Plankton

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Annotated IFCB plankton images from the Mediterranean Sea.

Scientific data
The Imaging FlowCytobot (IFCB), supported by machine learning-based classifications, has revolutionized plankton research by automating plankton monitoring and considerably increasing sampling resolution. However, building a training set of labeled I...

Unraveling long-term health dynamics of impounded lakes integrating water diversion-adapted planktonic index of biotic integrity and machine learning.

Environmental research
Assessing ecosystem integrity of impounded lakes subjected to sustained water diversion is fundamental for advancing adaptive water governance. Nevertheless, drivers of lake health variation under recurrent flow regulation, particularly their multisc...

Design of a fractional-order environmental toxin-plankton system in aquatic ecosystems: A novel machine predictive expedition with nonlinear autoregressive neuroarchitectures.

Water research
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...

Intelligent Detection and Recognition of Marine Plankton by Digital Holography and Deep Learning.

Sensors (Basel, Switzerland)
The detection, observation, recognition, and statistics of marine plankton are the basis of marine ecological research. In recent years, digital holography has been widely applied to plankton detection and recognition. However, the recording and reco...

Predicting thermodynamic adhesion energies of membrane fouling in planktonic anammox MBR via backpropagation neural network model.

Bioresource technology
Predicting thermodynamic adhesion energies was a critical strategy for mitigating membrane fouling. This study utilized a backpropagation (BP) neural network model to predict the thermodynamic adhesion energies associated with membrane fouling in a p...

In-domain versus out-of-domain transfer learning in plankton image classification.

Scientific reports
Plankton microorganisms play a huge role in the aquatic food web. Recently, it has been proposed to use plankton as a biosensor, since they can react to even minimal perturbations of the aquatic environment with specific physiological changes, which ...

Deep-Learning-Based Automated Tracking and Counting of Living Plankton in Natural Aquatic Environments.

Environmental science & technology
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...

Hierarchical deep learning model to simulate phytoplankton at phylum/class and genus levels and zooplankton at the genus level.

Water research
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...

Main-Chain Sulfonium-Containing Homopolymers with Negligible Hemolytic Toxicity for Eradication of Bacterial and Fungal Biofilms.

ACS macro letters
Antimicrobials against planktonic cells and established biofilms at low doses are in increasing demand to tackle antibiotic-resistant biofilm infections. As a promising alternative to antibiotics, cationic polymers can effectively kill planktonic mic...

Machine Learning for the Study of Plankton and Marine Snow from Images.

Annual review of marine science
Quantitative imaging instruments produce a large number of images of plankton and marine snow, acquired in a controlled manner, from which the visual characteristics of individual objects and their in situ concentrations can be computed. To exploit t...