{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:40:37Z","timestamp":1777336837862,"version":"3.51.4"},"reference-count":55,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100010801","name":"Xunta de Galicia","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010801","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1016\/j.cmpb.2020.105923","type":"journal-article","created":{"date-parts":[[2021,1,14]],"date-time":"2021-01-14T21:37:53Z","timestamp":1610660273000},"page":"105923","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":24,"special_numbering":"C","title":["Fully automatic detection and classification of phytoplankton specimens in digital microscopy images"],"prefix":"10.1016","volume":"200","author":[{"given":"David","family":"Rivas-Villar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4407-9091","authenticated-orcid":false,"given":"Jos\u00e9","family":"Rouco","sequence":"additional","affiliation":[]},{"given":"Rafael","family":"Carballeira","sequence":"additional","affiliation":[]},{"given":"Manuel G.","family":"Penedo","sequence":"additional","affiliation":[]},{"given":"Jorge","family":"Novo","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.cmpb.2020.105923_bib0001","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.trac.2016.06.023","article-title":"A review of monitoring technologies for real-time management of cyanobacteria: recent advances and future direction","volume":"85","author":"Zamyadi","year":"2016","journal-title":"TrAC, Trends Anal. Chem."},{"issue":"5","key":"10.1016\/j.cmpb.2020.105923_bib0002","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1016\/j.watres.2011.08.002","article-title":"Climate change: links to global expansion of harmful cyanobacteria","volume":"46","author":"Paerl","year":"2012","journal-title":"Water Res."},{"issue":"12","key":"10.1016\/j.cmpb.2020.105923_bib0003","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1093\/plankt\/fbs068","article-title":"Performance of the human \u201dcounting machine\u201d: evaluation of manual microscopy for enumerating plankton","volume":"34","author":"First","year":"2012","journal-title":"J. Plankton Res."},{"key":"10.1016\/j.cmpb.2020.105923_bib0004","series-title":"Automatic Diatom Identification","first-page":"75","article-title":"Human Error and Quality Assurance in Diatom Analysis","volume":"51","author":"Kelly","year":"2002"},{"key":"10.1016\/j.cmpb.2020.105923_bib0005","first-page":"561","article-title":"Intercalibrations of freshwater phytoplankton analyses","volume":"12","author":"Vuorio","year":"2007","journal-title":"Boreal Environ. Res."},{"key":"10.1016\/j.cmpb.2020.105923_bib0006","doi-asserted-by":"crossref","first-page":"17","DOI":"10.3354\/meps247017","article-title":"Do experts make mistakes? a comparison of human and machine identification of dinoflagellates","volume":"247","author":"Culverhouse","year":"2003","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"10.1016\/j.cmpb.2020.105923_bib0007","doi-asserted-by":"crossref","first-page":"409","DOI":"10.3389\/fmars.2018.00409","article-title":"Addressing the problem of harmful algal blooms in latin america and the caribbean- a regional network for early warning and response","volume":"5","author":"Cuellar-Martinez","year":"2018","journal-title":"Front. Mar. Sci."},{"key":"10.1016\/j.cmpb.2020.105923_bib0008","first-page":"67","article-title":"The video plankton recorder (vpr): design and initial results","volume":"36","author":"Davis","year":"1992","journal-title":"Arch. Hydrobiol. Beih. Ergebn. Limnol."},{"issue":"7","key":"10.1016\/j.cmpb.2020.105923_bib0009","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.1016\/S0967-0645(96)00051-3","article-title":"Rapid visualization of plankton abundance and taxonomic composition using the video plankton recorder","volume":"43","author":"Davis","year":"1996","journal-title":"Deep Sea Res. Part II"},{"issue":"5067","key":"10.1016\/j.cmpb.2020.105923_bib0010","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1126\/science.257.5067.230","article-title":"Microaggregations of oceanic plankton observed by towed video microscopy","volume":"257","author":"Davis","year":"1992","journal-title":"Science"},{"key":"10.1016\/j.cmpb.2020.105923_bib0011","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1109\/48.972110","article-title":"A system for high-resolution zooplankton imaging","volume":"26","author":"Samson","year":"2001","journal-title":"Oceanic Engineering, IEEE Journal of"},{"key":"10.1016\/j.cmpb.2020.105923_bib0012","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/S0967-0637(03)00003-7","article-title":"An automated submersible flow cytometer for analyzing pico- and nanophytoplankton: flowcytobot","volume":"50","author":"Olson","year":"2003","journal-title":"Deep Sea Res. Part I"},{"key":"10.1016\/j.cmpb.2020.105923_bib0013","series-title":"2014\u00a0IEEE\/OES Autonomous Underwater Vehicles (AUV)","first-page":"1","article-title":"Development of a realtime plankton image archiver for AUVs","author":"Nagashima","year":"2014"},{"key":"10.1016\/j.cmpb.2020.105923_bib0014","doi-asserted-by":"crossref","first-page":"285","DOI":"10.3354\/meps168285","article-title":"An imaging-in-flow system for automated analysis of marine microplankton","volume":"168","author":"Sieracki","year":"1998","journal-title":"Marine Ecology-progress Series - MAR ECOL-PROGR SER"},{"key":"10.1016\/j.cmpb.2020.105923_bib0015","series-title":"Imaging flow cytometry: Methods and protocols, methods in molecular biology, vol. 1389","author":"Barteneva","year":"2016"},{"issue":"11","key":"10.1016\/j.cmpb.2020.105923_bib0016","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1049\/iet-ipr.2017.0127","article-title":"Robust and automatic cell detection and segmentation from microscopic images of non-setae phytoplankton species","volume":"11","author":"Zheng","year":"2017","journal-title":"IET Image Proc."},{"issue":"4","key":"10.1016\/j.cmpb.2020.105923_bib0017","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1016\/j.patcog.2011.10.019","article-title":"Phase congruency-based detection of circular objects applied to analysis of phytoplankton images","volume":"45","author":"Verikas","year":"2012","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.cmpb.2020.105923_bib0018","unstructured":"Woods hole oceanographic institution plankton, (https:\/\/darchive.mblwhoilibrary.org\/handle\/1912\/7341). Accessed: 2020-07-29."},{"key":"10.1016\/j.cmpb.2020.105923_bib0019","unstructured":"Kaggle national data science bowl, (https:\/\/www.kaggle.com\/c\/datasciencebowl\/data). Accessed: 2020-07-29."},{"key":"10.1016\/j.cmpb.2020.105923_bib0020","series-title":"2016 5th Brazilian Conference on Intelligent Systems (BRACIS)","first-page":"49","article-title":"Supervised Microalgae Classification in Imbalanced Dataset","author":"Corr\u00e9a","year":"2016"},{"key":"10.1016\/j.cmpb.2020.105923_bib0021","series-title":"2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)","first-page":"20","article-title":"Deep Learning for Microalgae Classification","author":"Correa","year":"2017"},{"issue":"6","key":"10.1016\/j.cmpb.2020.105923_bib0022","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1093\/plankt\/fbs017","article-title":"Improvement of plankton biovolume estimates derived from image-based automatic sampling devices: application to flowcam","volume":"34","author":"\u00c1lvarez","year":"2012","journal-title":"J. Plankton Res."},{"issue":"4","key":"10.1016\/j.cmpb.2020.105923_bib0023","doi-asserted-by":"crossref","first-page":"1753","DOI":"10.1109\/TSMCB.2004.830340","article-title":"Recognizing plankton images from the shadow image particle profiling evaluation recorder","volume":"34","author":"Tong Luo","year":"2004","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)"},{"key":"10.1016\/j.cmpb.2020.105923_bib0024","series-title":"2005\u00a0IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905) - Workshops","first-page":"47","article-title":"Combining Local and Global Image Features for Object Class Recognition","author":"Lisin","year":"2005"},{"key":"10.1016\/j.cmpb.2020.105923_bib0025","series-title":"2009\u00a0Pacific-Asia Conference on Circuits, Communications and Systems","first-page":"610","article-title":"A Research on the Recognition of Chironomid Larvae Based on SVM","author":"Zhao","year":"2009"},{"key":"10.1016\/j.cmpb.2020.105923_bib0026","doi-asserted-by":"crossref","first-page":"21","DOI":"10.3354\/meps295021","article-title":"Automatic plankton image recognition with co-occurrence matrices and support vector machine","volume":"295","author":"Hu","year":"2005","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"10.1016\/j.cmpb.2020.105923_bib0027","doi-asserted-by":"crossref","first-page":"47","DOI":"10.3354\/meps195047","article-title":"Identification of 72 phytoplankton species by radial basis function neural network analysis of flow cytometric data","volume":"195","author":"Boddy","year":"2000","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"10.1016\/j.cmpb.2020.105923_bib0028","doi-asserted-by":"crossref","first-page":"281","DOI":"10.3354\/meps139281","article-title":"Automatic classification of field-collected dinoflagellates by artificial neural network","volume":"139","author":"Pf","year":"1996","journal-title":"Mar. Ecol. Prog. Ser."},{"issue":"6","key":"10.1016\/j.cmpb.2020.105923_bib0029","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1093\/plankt\/25.6.669","article-title":"Automated counting of phytoplankton by pattern recognition: a comparison with a manual counting method","volume":"25","author":"Embleton","year":"2003","journal-title":"J. Plankton Res."},{"key":"10.1016\/j.cmpb.2020.105923_bib0030","series-title":"2017\u00a0IEEE Winter Conference on Applications of Computer Vision (WACV)","first-page":"1082","article-title":"Transfer Learning and Deep Feature Extraction for Planktonic Image Data Sets","author":"Orenstein","year":"2017"},{"key":"10.1016\/j.cmpb.2020.105923_bib0031","series-title":"2016\u00a0IEEE International Conference on Image Processing (ICIP)","first-page":"3713","article-title":"Plankton classification on imbalanced large scale database via convolutional neural networks with transfer learning","author":"Lee","year":"2016"},{"key":"10.1016\/j.cmpb.2020.105923_bib0032","series-title":"2017 IEEE Winter Conference on Applications of Computer Vision (WACV)","first-page":"1082","article-title":"Transfer learning and deep feature extraction for planktonic image data sets","author":"Orenstein","year":"2017"},{"issue":"4","key":"10.1016\/j.cmpb.2020.105923_bib0033","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1093\/plankt\/fbz023","article-title":"Automatic plankton quantification using deep features","volume":"41","author":"Gonz\u00e1lez","year":"2019","journal-title":"J. Plankton Res."},{"key":"10.1016\/j.cmpb.2020.105923_bib0034","series-title":"Advances in Neural Information Processing Systems 25","first-page":"1097","article-title":"Imagenet Classification with Deep Convolutional Neural Networks","author":"Krizhevsky","year":"2012"},{"key":"10.1016\/j.cmpb.2020.105923_bib0035","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.cmpb.2020.105923_bib0036","series-title":"2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"248","article-title":"Imagenet: A large-scale hierarchical image database","author":"Deng","year":"2009"},{"issue":"9","key":"10.1016\/j.cmpb.2020.105923_bib0037","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1002\/jemt.20338","article-title":"Automatic analysis of aqueous specimens for phytoplankton structure recognition and population estimation","volume":"69","author":"Rodenacker","year":"2006","journal-title":"Microsc. Res. Tech."},{"issue":"2","key":"10.1016\/j.cmpb.2020.105923_bib0038","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/s00138-014-0643-0","article-title":"A novel technique to extract accurate cell contours applied for segmentation of phytoplankton images","volume":"26","author":"Gelzinis","year":"2015","journal-title":"Mach. Vis. Appl."},{"key":"10.1016\/j.cmpb.2020.105923_sbref0039","article-title":"WHOI-Plankton- A Large Scale Fine Grained Visual Recognition Benchmark Dataset for Plankton Classification","author":"Orenstein","year":"2015","journal-title":"arXiv:1510.00745 [cs]"},{"issue":"1","key":"10.1016\/j.cmpb.2020.105923_bib0040","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1186\/1471-2105-14-115","article-title":"Planktovision - an automated analysis system for the identification of phytoplankton","volume":"14","author":"Schulze","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.cmpb.2020.105923_bib0041","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.marpol.2017.05.022","article-title":"From microscope to management: the critical value of plankton taxonomy to marine policy and biodiversity conservation","volume":"83","author":"McQuatters-Gollop","year":"2017","journal-title":"Mar Policy"},{"key":"10.1016\/j.cmpb.2020.105923_bib0042","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1002\/jemt.20338","article-title":"Automatic analysis of aqueous specimens for phytoplankton structure recognition and population estimation","volume":"69","author":"Rodenacker","year":"2006","journal-title":"Microsc. Res. Tech."},{"key":"10.1016\/j.cmpb.2020.105923_bib0043","doi-asserted-by":"crossref","first-page":"106395","DOI":"10.1016\/j.ecolind.2020.106395","article-title":"Identification and enumeration of cyanobacteria species using a deep neural network","volume":"115","author":"Baek","year":"2020","journal-title":"Ecol. Indic."},{"key":"10.1016\/j.cmpb.2020.105923_bib0044","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1080\/2151237X.2007.10129236","article-title":"Adaptive thresholding using the integral image","volume":"12","author":"Bradley","year":"2007","journal-title":"J. Graphics Tools"},{"issue":"1","key":"10.1016\/j.cmpb.2020.105923_bib0045","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/0734-189X(85)90016-7","article-title":"Topological structural analysis of digitized binary images by border following","volume":"30","author":"Suzuki","year":"1985","journal-title":"Computer Vision, Graphics, and Image Processing"},{"key":"10.1016\/j.cmpb.2020.105923_bib0046","first-page":"793","article-title":"Sur la sph\u00ebre vide","volume":"6","author":"Delaunay","year":"1934","journal-title":"Bulletin de l\u2019Acad\u00e9mie des Sciences de l\u2019URSS, Classe des Sciences Math\u00e9matiques et Naturelles"},{"key":"10.1016\/j.cmpb.2020.105923_bib0047","series-title":"Computational geometry: Algorithms and applications","author":"Berg","year":"2008"},{"key":"10.1016\/j.cmpb.2020.105923_bib0048","series-title":"Tenth IEEE International Conference on Computer Vision (ICCV\u201905) Volume 1","first-page":"1800","article-title":"Object categorization by learned universal visual dictionary","volume":"2","author":"Winn","year":"2005"},{"key":"10.1016\/j.cmpb.2020.105923_bib0049","series-title":"2012 10th IAPR International Workshop on Document Analysis Systems","first-page":"297","article-title":"Word image retrieval using bag of visual words","author":"Shekhar","year":"2012"},{"issue":"1","key":"10.1016\/j.cmpb.2020.105923_bib0050","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1109\/TMM.2011.2170665","article-title":"An enhanced bag-of-visual word vector space model to represent visual content in athletics images","volume":"14","author":"Kesorn","year":"2012","journal-title":"IEEE Trans Multimedia"},{"key":"10.1016\/j.cmpb.2020.105923_sbref0051","series-title":"2019International Joint Conference on Neural Networks (IJCNN)","first-page":"1","article-title":"Deep Feature Analysis in a Transfer Learning-based Approach for the Automatic Identification of Diabetic Macular Edema","author":"Moura","year":"2019"},{"key":"10.1016\/j.cmpb.2020.105923_bib0052","series-title":"Data clustering: Theory, algorithms, and applications","volume":"20","author":"Ma","year":"2007"},{"issue":"2","key":"10.1016\/j.cmpb.2020.105923_bib0053","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/BF00341922","article-title":"Texture discrimination by gabor functions","volume":"55","author":"Turner","year":"1986","journal-title":"Biol. Cybern."},{"issue":"9","key":"10.1016\/j.cmpb.2020.105923_bib0054","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1016\/S0167-8655(02)00056-9","article-title":"Texture classification using gabor filters","volume":"23","author":"Idrissa","year":"2002","journal-title":"Pattern Recognit Lett"},{"key":"10.1016\/j.cmpb.2020.105923_bib0055","series-title":"Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis, Advances in ubiquitous sensing applications for healthcare","first-page":"31","article-title":"Chapter 2 - Use of Health-related Indices and Classification Methods in Medical Data","author":"Bersimis","year":"2019"}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260720317569?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260720317569?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T03:58:28Z","timestamp":1759204708000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260720317569"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3]]},"references-count":55,"alternative-id":["S0169260720317569"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2020.105923","relation":{},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2021,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Fully automatic detection and classification of phytoplankton specimens in digital microscopy images","name":"articletitle","label":"Article Title"},{"value":"Computer Methods and Programs in Biomedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cmpb.2020.105923","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"105923"}}