Nothing Special   »   [go: up one dir, main page]

Le et al., 2022 - Google Patents

Benchmarking and automating the image recognition capability of an In situ plankton imaging system

Le et al., 2022

View HTML
Document ID
1860505246921570556
Author
Le K
Yuan Z
Syed A
Ratelle D
Orenstein E
Carter M
Strang S
Kenitz K
Morgado P
Franks P
Vasconcelos N
Jaffe J
Publication year
Publication venue
Frontiers in Marine Science

External Links

Snippet

To understand ocean health, it is crucial to monitor photosynthetic marine plankton–the microorganisms that form the base of the marine food web and are responsible for the uptake of atmospheric carbon. With the recent development of in situ microscopes that can …
Continue reading at www.frontiersin.org (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N15/1468—Electro-optical investigation, e.g. flow cytometers with spatial resolution of the texture or inner structure of the particle
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N15/1456—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G01N15/1459—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals the analysis being performed on a sample stream
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/84—Systems specially adapted for particular applications
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N1/00—Sampling; Preparing specimens for investigation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Cowger et al. Critical review of processing and classification techniques for images and spectra in microplastic research
Irisson et al. Machine learning for the study of plankton and marine snow from images
Knausgård et al. Temperate fish detection and classification: a deep learning based approach
Goodwin et al. Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook
Lorenzo-Navarro et al. SMACC: A system for microplastics automatic counting and classification
Davis et al. Real-time observation of taxa-specific plankton distributions: an optical sampling method
Bi et al. A semi-automated image analysis procedure for in situ plankton imaging systems
Pennekamp et al. Implementing image analysis in laboratory‐based experimental systems for ecology and evolution: a hands‐on guide
Leow et al. Automated identification of copepods using digital image processing and artificial neural network
Le et al. Benchmarking and automating the image recognition capability of an In situ plankton imaging system
Dyomin et al. Monitoring of plankton spatial and temporal characteristics with the use of a submersible digital holographic camera
Toda et al. DeepStomata: facial recognition technology for automated stomatal aperture measurement
EP4091135A1 (en) Non-tumor segmentation to support tumor detection and analysis
Panaïotis et al. Content-aware segmentation of objects spanning a large size range: application to plankton images
Dyomin et al. Fast recognition of marine particles in underwater digital holography
Vaughan et al. A review of microscopic cell imaging and neural network recognition for synergistic cyanobacteria identification and enumeration
Høye et al. Accurate image-based identification of macroinvertebrate specimens using deep learning—How much training data is needed?
Barua et al. In situ digital holographic microscopy for rapid detection and monitoring of the harmful dinoflagellate, Karenia brevis
Chen et al. Deep-learning-based automated tracking and counting of living plankton in natural aquatic environments
Zhu et al. Smart polarization and spectroscopic holography for real-time microplastics identification
Singh et al. Neural network model approach for automated benthic animal identification
Yilmaz et al. Marine mucilage mapping with explained deep learning model using water-related spectral indices: a case study of Dardanelles Strait, Turkey
Phan et al. Exploiting weak supervision to facilitate segmentation, classification, and analysis of microplastics (< 100 μm) using Raman microspectroscopy images
Witmer et al. Generative adversarial networks for morphological–temporal classification of stem cell images
Ranolo et al. Underwater and coastal seaweeds detection for fluorescence seaweed photos and videos using YOLOV3 and YOLOV5