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Automated plankton image analysis using convolutional neural networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Shadow cinematography of fish larvae
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Automated sizing, counting and identification of zooplankton by pattern recognition
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In-situ silhouette photography of Gulf Stream zooplankton
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COMPUTER-PROCESSING OF ZOOPLANKTON SAMPLES
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Methods of training set construction: Towards improving performance for automated mesozooplankton image classification systems
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Aggregates and their distributions determined from LOPC observations made using an autonomous profiling float
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Phytoplankton assemblage structure in and around a massive under-ice bloom in the Chukchi Sea
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The LOKI underwater imaging system and an automatic identification model for the detection of zooplankton taxa in the Arctic Ocean
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Imperfect automatic image classification successfully describes plankton distribution patterns
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Larval assemblages of large and medium-sized pelagic species in the Straits of Florida
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From the Hensen net toward four-dimensional biological oceanography
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Distribution of plankton, particles, and hydrographic features across Georges Bank described using the Video Plankton Recorder
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Handbook of Scaling Methods in Aquatic Ecology: Measurement, Analysis, Simulation
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Resolution of fine biological structure including small narcomedusae across a front in the Southern California Bight
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Silhouette photography of oceanic zooplankton
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In situ imaging reveals the biomass of giant protists in the global ocean
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Rotation-invariant convolutional neural networks for galaxy morphology prediction
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Optimizing the number of classes in automated zooplankton classification
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Digital zooplankton image analysis using the ZooScan integrated system
inferredcites →https://doi.org/10.1093/plankt/fbs028openalex-snapshot
Mesozooplankton and particulate matter responses to a deep-water frontal system in the southern California Current System
inferredcites →https://doi.org/10.1093/plankt/fbt056openalex-snapshot
Relationships between phytoplankton thin layers and the fine-scale vertical distributions of two trophic levels of zooplankton
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A system for high-resolution zooplankton imaging
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Face recognition: a convolutional neural-network approach
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Active learning to recognize multiple types of plankton
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Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
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Image Analysis Techniques to Accompany a new In Situ Ichthyoplankton Imaging System
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Reorganization of North Atlantic Marine Copepod Biodiversity and Climate
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Transatlantic Abundance of the N 2 -Fixing Colonial Cyanobacterium Trichodesmium
inferredcites →https://doi.org/10.1126/science.aac5605openalex-snapshot
Tara Oceans studies plankton at planetary scale
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1371/journal.pone.0127121openalex-snapshot
A Semi-Automated Image Analysis Procedure for In Situ Plankton Imaging Systems
inferredcites →https://doi.org/10.3354/meps079303openalex-snapshot
Biological pattern recognition by neural networks
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Environmental drivers of the fine-scale distribution of a gelatinous zooplankton community across a mesoscale front
inferredcites →https://doi.org/10.3354/meps139281openalex-snapshot
Automatic classification of field-collected dinoflagellates by artificial neural network
inferredcites →https://doi.org/10.3354/meps284077openalex-snapshot
Real-time observation of taxa-specific plankton distributions: an optical sampling method
inferredcites →https://doi.org/10.3354/meps295021openalex-snapshot
Automatic plankton image recognition with co-occurrence matrices and Support Vector Machine
inferredcites →https://doi.org/10.3354/meps306051openalex-snapshot
Accurate automatic quantification of taxa-specific plankton abundance using dual classification with correction
inferredcites →https://doi.org/10.3354/meps312297openalex-snapshot
AS WE SEE IT* Automatic image analysis of plankton: future perspectives
inferredcites →https://doi.org/10.3389/fmars.2017.00082openalex-snapshot
A Tale of Two Crowds: Public Engagement in Plankton Classification
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In situ ichthyoplankton imaging system ( I SIIS): system design and preliminary results
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The Underwater Vision Profiler 5: An advanced instrument for high spatial resolution studies of particle size spectra and zooplankton
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Sparse 3D convolutional neural networks
inferredcites →https://doi.org/10.5555/1046920.1088692openalex-snapshot
Active Learning to Recognize Multiple Types of Plankton
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Evaluation of the In Situ Ichthyoplankton Imaging System (ISIIS): comparison with the traditional (bongo net) sampler
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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The Scripps Plankton Camera system: A framework and platform for in situ microscopy
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Globally Consistent Quantitative Observations of Planktonic Ecosystems
inferred← citeshttps://doi.org/10.3389/fmars.2019.00399openalex-snapshot
Considerations in Harmful Algal Bloom Research and Monitoring: Perspectives From a Consensus-Building Workshop and Technology Testing
inferred← citeshttps://doi.org/10.3389/fmars.2019.00778openalex-snapshot
Estimating Carbon Flux From Optically Recording Total Particle Volume at Depths Below the Primary Pycnocline
inferred← citeshttps://doi.org/10.3389/fmars.2019.00834openalex-snapshot
Sinking Organic Particles in the Ocean—Flux Estimates From in situ Optical Devices
inferred← citeshttps://doi.org/10.3389/fmars.2020.00254openalex-snapshot
Multi-Instrument Assessment of Phytoplankton Abundance and Cell Sizes in Mono-Specific Laboratory Cultures and Whole Plankton Community Composition in the North Atlantic
inferred← citeshttps://doi.org/10.3389/fmars.2020.542701openalex-snapshot
High-Resolution Sampling of a Broad Marine Life Size Spectrum Reveals Differing Size- and Composition-Based Associations With Physical Oceanographic Structure
inferred← citeshttps://doi.org/10.3389/fmars.2021.701793openalex-snapshot
Principles and Methods of Counteracting Harmful Salmon–Arthropod Interactions in Salmon Farming: Addressing Possibilities, Limitations, and Future Options
inferred← citeshttps://doi.org/10.3389/fmars.2021.733799openalex-snapshot
Total Water Column Analysis Shows the Importance of a Single Species in Subsurface Chlorophyll Maximum Thin Layers in Stratified Waters
inferred← citeshttps://doi.org/10.3389/fmars.2022.867695openalex-snapshot
Towards operational phytoplankton recognition with automated high-throughput imaging, near-real-time data processing, and convolutional neural networks
inferred← citeshttps://doi.org/10.3389/fmars.2022.868420openalex-snapshot
Automated Plankton Classification With a Dynamic Optimization and Adaptation Cycle
inferred← citeshttps://doi.org/10.3389/fmars.2022.869088openalex-snapshot
Benchmarking and Automating the Image Recognition Capability of an In Situ Plankton Imaging System
inferred← citeshttps://doi.org/10.3389/fmars.2022.870005openalex-snapshot
Content-Aware Segmentation of Objects Spanning a Large Size Range: Application to Plankton Images
inferred← citeshttps://doi.org/10.3389/fmars.2022.878803openalex-snapshot
Coupling Imaging and Omics in Plankton Surveys: State-of-the-Art, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.3389/fmars.2023.1157370openalex-snapshot
Demystifying image-based machine learning: a practical guide to automated analysis of field imagery using modern machine learning tools
inferred← citeshttps://doi.org/10.3389/fmars.2023.1166629openalex-snapshot
Drivers of plankton community structure in intermittent and continuous coastal upwelling systems–from microbes and microscale in-situ imaging to large scale patterns
inferred← citeshttps://doi.org/10.3389/fmars.2023.1186343openalex-snapshot
Toward efficient deep learning system for in-situ plankton image recognition
inferred← citeshttps://doi.org/10.3389/fmars.2023.1187771openalex-snapshot
Edge computing at sea: high-throughput classification of in-situ plankton imagery for adaptive sampling
inferred← citeshttps://doi.org/10.3389/fmars.2023.1280510openalex-snapshot
DeepLOKI- a deep learning based approach to identify zooplankton taxa on high-resolution images from the optical plankton recorder LOKI
inferred← citeshttps://doi.org/10.3389/fmars.2025.1539828openalex-snapshot
Optimizing an image analysis protocol for ocean particles in focused shadowgraph imaging systems
inferred← citeshttps://doi.org/10.3389/fmars.2025.1699781openalex-snapshot
Automated image classification workflow for phytoplankton monitoring
inferred← citeshttps://doi.org/10.3389/fmars.2025.1729254openalex-snapshot
Self-supervised transfer learning for few-shot classification on marine plankton images
inferred← citeshttps://doi.org/10.3389/fmars.2026.1805062openalex-snapshot
Combatting the data crisis: a primer on using artificial intelligence in marine biodiversity
inferred← citeshttps://doi.org/10.3389/fmars.2026.1882482openalex-snapshot
Plankton imager 10 monitoring in the southern North Sea: an open workflow for classification, morphometry and DwC-A publication
inferred← citeshttps://doi.org/10.3389/fmicb.2021.746297openalex-snapshot
Deep Learning Classification of Lake Zooplankton
inferred← citeshttps://doi.org/10.3390/ijms26094234openalex-snapshot
TFProtBert: Detection of Transcription Factors Binding to Methylated DNA Using ProtBert Latent Space Representation
inferred← citeshttps://doi.org/10.3390/oceans6010007openalex-snapshot
IchthyNet: An Ensemble Method for the Classification of In Situ Marine Zooplankton Shadowgraph Images
inferred← citeshttps://doi.org/10.3390/w16152160openalex-snapshot
Computer Vision Techniques for Morphological Analysis and Identification of Two Pseudo-nitzschia Species
inferred← citeshttps://doi.org/10.37828/em.2026.100.4openalex-snapshot
Application of modern mathematical methods for species discrimination in the water fleas (Cladocera: Branchiopoda): case of Bosmina (Bosmina) longirostris (O.F. Müller, 1776) from Europe and Sakhalin Island
inferred← citeshttps://doi.org/10.38124/ijsrmt.v4i9.805openalex-snapshot
A Comparative Study of DETR and YOLOv8n for Plankton Detection and Classification in the Makassar River
inferred← citeshttps://doi.org/10.48550/arxiv.1909.11380openalex-snapshot
Beyond image classification: zooplankton identification with deep vector space embeddings
inferred← citeshttps://doi.org/10.5194/amt-15-5141-2022openalex-snapshot
Ice crystal images from optical array probes: classification with convolutional neural networks
inferred← citeshttps://doi.org/10.5194/essd-16-2971-2024openalex-snapshot
First release of the Pelagic Size Structure database: global datasets of marine size spectra obtained from plankton imaging devices
inferred← citeshttps://doi.org/10.5194/essd-18-945-2026openalex-snapshot
Benchmark of plankton images classification: emphasizing features extraction over classifier complexity
inferred← citeshttps://doi.org/10.5194/essd-2023-479-ac2openalex-snapshot
Reply on RC1, with corrected line numbers for each comment
inferred← citeshttps://doi.org/10.5194/essd-2025-309-supplementopenalex-snapshot
Supplementary material to "Benchmark of plankton images classification: emphasizing features extraction over classifier complexity"
inferred← citeshttps://doi.org/10.5194/os-2020-62openalex-snapshot
Towards operational phytoplankton recognition with automated high-throughput imaging and compact convolutional neural networks
inferred← citeshttps://doi.org/10.53106/199115992023043402009openalex-snapshot
Research on Rip Currents Detection Method Based on Improved YOLOv5s
inferred← citeshttps://doi.org/10.6084/m9.figshare.14795399openalex-snapshot
Additional file 1 of Plankton classification with high-throughput submersible holographic microscopy and transfer learning
inferred← citeshttps://doi.org/10.64898/2026.06.23.733833openalex-snapshot
Volumetric Flow Imaging Microscopy to Enhance Particle Characterization
inferred← citeshttps://doi.org/10.70675/3e93bda2zb3dbz44bfz9996z42a07afb819dopenalex-snapshot
Automatic Classification Tool for Optical Array Probes to Understand Ice Cloud Mechanisms
inferred← citeshttps://doi.org/10.70675/6b0e91c7zd2ebz4dfaza925z8de56d803e02openalex-snapshot
Towards a new insight of the carbon transport in the global ocean
inferred← citeshttps://doi.org/10.70675/c540fe35z8790z4882zbd81z30a0e31bcd4copenalex-snapshot
Plankton distribution across scales : contributions from artificial intelligence to plankton ecology
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.