{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T22:17:09Z","timestamp":1742941029904,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031483158"},{"type":"electronic","value":"9783031483165"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-48316-5_28","type":"book-chapter","created":{"date-parts":[[2023,11,22]],"date-time":"2023-11-22T00:03:08Z","timestamp":1700611388000},"page":"280-292","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Image Analysis for Microalgae Identification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2352-1952","authenticated-orcid":false,"given":"Jeffrey","family":"Soar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3006-1958","authenticated-orcid":false,"given":"Oh Shu","family":"Lih","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3114-6523","authenticated-orcid":false,"given":"Loh Hui","family":"Wen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4549-0704","authenticated-orcid":false,"given":"Aletha","family":"Ward","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3692-382X","authenticated-orcid":false,"given":"Ekta","family":"Sharma","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2290-6749","authenticated-orcid":false,"given":"Ravinesh C.","family":"Deo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5117-8333","authenticated-orcid":false,"given":"Prabal Datta","family":"Barua","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2086-6517","authenticated-orcid":false,"given":"Ru-San","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Eliezer","family":"Rinen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2689-8552","authenticated-orcid":false,"given":"U Rajendra","family":"Acharya","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,22]]},"reference":[{"key":"28_CR1","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1007\/978-3-642-28451-9_22","volume-title":"Seaweed Biology: Novel Insights into Ecophysiology, Ecology and Utilization","author":"CM Buchholz","year":"2012","unstructured":"Buchholz, C.M., Krause, G., Buck, B.H.: Seaweed and man. In: Wiencke, C., Bischof, K. (eds.) Seaweed Biology: Novel Insights into Ecophysiology, Ecology and Utilization, pp. 471\u2013493. Springer Berlin Heidelberg, Berlin, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-28451-9_22"},{"key":"28_CR2","doi-asserted-by":"publisher","unstructured":"Merz, C., Main, K.: Microalgae (diatom) production\u2014the aquaculture and biofuel nexus. In: Oceans\u201914 MTS\/IEEE Conference Proceedings \u2013 IEEE Xplore, St. John's, NL, Canada (2014). https:\/\/doi.org\/10.1109\/OCEANS.2014.7003242","DOI":"10.1109\/OCEANS.2014.7003242"},{"key":"28_CR3","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1080\/09670262.2017.1365273","volume":"52","author":"M Mac Monagail","year":"2017","unstructured":"Mac Monagail, M., Cornish, L., Morrison, L., Ara\u00fajo, R., Critchley, A.T.: Sustainable harvesting of wild seaweed resources. Eur. J. Phycol. 52, 371\u2013390 (2017). https:\/\/doi.org\/10.1080\/09670262.2017.1365273","journal-title":"Eur. J. Phycol."},{"key":"28_CR4","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.1016\/j.foodchem.2005.11.029","volume":"100","author":"S Marsham","year":"2007","unstructured":"Marsham, S., Scott, G.W., Tobin, M.L.: Comparison of nutritive chemistry of a range of temperate seaweeds. Food Chem. 100, 1331\u20131336 (2007). https:\/\/doi.org\/10.1016\/j.foodchem.2005.11.029","journal-title":"Food Chem."},{"key":"28_CR5","doi-asserted-by":"publisher","unstructured":"Cai, J., et al.: Seaweeds and microalgae: an overview for unlocking their potential in global aquaculture development. FAO Fisheries and Aquaculture Circular (1229) (2021). https:\/\/doi.org\/10.4060\/cb5670en","DOI":"10.4060\/cb5670en"},{"key":"28_CR6","doi-asserted-by":"publisher","unstructured":"Griffiths, M.J., Harrison, S.T.L.: Lipid productivity as a key characteristic for choosing algal species for biodiesel production. J. Appl. Phycol. 21, 493\u2013507 (2009). https:\/\/doi.org\/10.1007\/s10811-008-9392-7","DOI":"10.1007\/s10811-008-9392-7"},{"key":"28_CR7","doi-asserted-by":"publisher","unstructured":"Andrade, D.S., et al.: Microalgae: cultivation, biotechnological, environmental, and agricultural applications. In: Maddela, N.R., Garc\u00eda, L.C., Cruzatty, S.C. (eds.) Advances in the Domain of Environmental Biotechnology: Microbiological Developments in Industries, Wastewater Treatment and Agriculture, pp. 635\u2013701. Springer Singapore, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-15-8999-7_23","DOI":"10.1007\/978-981-15-8999-7_23"},{"key":"28_CR8","doi-asserted-by":"publisher","unstructured":"Benedetti, M., Vecchi, V., Barera, S., Dall\u2019Osto, L.: Biomass from microalgae: the potential of domestication towards sustainable biofactories. Microb. Cell Fact. 17 (2018). https:\/\/doi.org\/10.1186\/s12934-018-1019-3","DOI":"10.1186\/s12934-018-1019-3"},{"key":"28_CR9","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/s11120-011-9638-0","volume":"109","author":"PJ McGinn","year":"2011","unstructured":"McGinn, P.J., Dickinson, K.E., Bhatti, S., Frigon, J.-C., Guiot, S.R., O\u2019Leary, S.J.B.: Integration of microalgae cultivation with industrial waste remediation for biofuel and bioenergy production: opportunities and limitations. Photosynth. Res. 109, 231\u2013247 (2011). https:\/\/doi.org\/10.1007\/s11120-011-9638-0","journal-title":"Photosynth. Res."},{"key":"28_CR10","doi-asserted-by":"publisher","unstructured":"Caporgno, M.P., Mathys, A.: Trends in microalgae incorporation into innovative food products with potential health benefits. Front. Nutr. 5 (2018). https:\/\/doi.org\/10.3389\/fnut.2018.00058","DOI":"10.3389\/fnut.2018.00058"},{"key":"28_CR11","unstructured":"Goondiwindi Regional Council. Communication of decision. mail@grc.qld.gov.au - Goondiwindi Regional Council. 27 November 2018 https:\/\/www.grc.qld.gov.au\/downloads\/file\/1028\/17-48g-decision-notice"},{"key":"28_CR12","doi-asserted-by":"publisher","first-page":"1255","DOI":"10.1016\/j.biotechadv.2018.04.004","volume":"36","author":"N Renuka","year":"2018","unstructured":"Renuka, N., Guldhe, A., Prasanna, R., Singh, P., Bux, F.: Microalgae as multi-functional options in modern agriculture: current trends, prospects and challenges. Biotechnol. Adv. 36, 1255\u20131273 (2018). https:\/\/doi.org\/10.1016\/j.biotechadv.2018.04.004","journal-title":"Biotechnol. Adv."},{"key":"28_CR13","doi-asserted-by":"publisher","first-page":"3723","DOI":"10.1007\/s10811-020-02241-x","volume":"32","author":"P Deore","year":"2020","unstructured":"Deore, P., Beardall, J., Noronha, S.: A perspective on the current status of approaches for early detection of microalgal grazing. J. Appl. Phycol. 32, 3723\u20133733 (2020). https:\/\/doi.org\/10.1007\/s10811-020-02241-x","journal-title":"J. Appl. Phycol."},{"key":"28_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2019\/4570808","volume":"2019","author":"Y He","year":"2019","unstructured":"He, Y., Zeng, H., Fan, Y., Ji, S., Wu, J.: Application of deep learning in integrated pest management: a real-time system for detection and diagnosis of oilseed rape pests. Mob. Inf. Syst. 2019, 1\u201314 (2019). https:\/\/doi.org\/10.1155\/2019\/4570808","journal-title":"Mob. Inf. Syst."},{"key":"28_CR15","doi-asserted-by":"publisher","first-page":"45301","DOI":"10.1109\/access.2019.2909522","volume":"7","author":"L Liu","year":"2019","unstructured":"Liu, L., et al.: PestNet: an end-to-end deep learning approach for large-scale multi-class pest detection and classification. IEEE Access 7, 45301\u201345312 (2019). https:\/\/doi.org\/10.1109\/access.2019.2909522","journal-title":"IEEE Access"},{"key":"28_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.biotechadv.2021.107819","volume":"54","author":"K Wang","year":"2022","unstructured":"Wang, K., et al.: How does the Internet of Things (IoT) help in microalgae biorefinery? Biotechnol. Adv. 54, 107819 (2022). https:\/\/doi.org\/10.1016\/j.biotechadv.2021.107819","journal-title":"Biotechnol. Adv."},{"key":"28_CR17","doi-asserted-by":"publisher","first-page":"2202","DOI":"10.1007\/s00343-022-1312-1","volume":"40","author":"W Xu","year":"2022","unstructured":"Xu, W., et al.: Identification of paralytic shellfish toxin-producing microalgae using machine learning and deep learning methods. J. Ocean. Limnol. 40, 2202\u20132217 (2022). https:\/\/doi.org\/10.1007\/s00343-022-1312-1","journal-title":"J. Ocean. Limnol."},{"key":"28_CR18","unstructured":"Austrade, Australian Government. Australia: shaping the future of food and agriculture. https:\/\/www.austrade.gov.au\/agriculture. Accessed 11 Feb 2022"},{"key":"28_CR19","unstructured":"Tan, M., Le, Q.: EfficientNetV2: smaller models and faster training. In Proceedings of the 38th International Conference on Machine Learning\/Proceedings of Machine Learning Research. PMLR 139, 14 December 2021. https:\/\/proceedings.mlr.press\/v139\/tan21a.html"},{"key":"28_CR20","unstructured":"Selvaraju, R.R., Das, A., Vedantam, R., Cogswell, M., Parikh, D., Batra, D.: Grad-CAM: Why did you say that?. arXiv preprint arXiv:1611.07450. 2016 Nov 22"},{"key":"28_CR21","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1007\/s11263-019-01228-7","volume":"128","author":"RR Selvaraju","year":"2020","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-CAM: visual explanations from deep networks via gradient-based localization. Int. J. Comput. Vis. 128, 336\u2013359 (2020). https:\/\/doi.org\/10.1007\/s11263-019-01228-7","journal-title":"Int. J. Comput. Vis."},{"key":"28_CR22","doi-asserted-by":"publisher","unstructured":"Zhang, Z.: Improved adam optimizer for deep neural networks. In: IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS) (2018). https:\/\/doi.org\/10.1109\/IWQoS.2018.8624183","DOI":"10.1109\/IWQoS.2018.8624183"},{"key":"28_CR23","doi-asserted-by":"publisher","first-page":"37281","DOI":"10.1364\/OE.438253","volume":"29","author":"J Luo","year":"2021","unstructured":"Luo, J., et al.: Confocal hyperspectral microscopic imager for the detection and classification of individual microalgae. Opt. Express 29, 37281 (2021). https:\/\/doi.org\/10.1364\/OE.438253","journal-title":"Opt. Express"},{"key":"28_CR24","doi-asserted-by":"publisher","first-page":"8872","DOI":"10.1021\/acs.analchem.1c01015","volume":"93","author":"M Heidari Baladehi","year":"2021","unstructured":"Heidari Baladehi, M., et al.: Culture-free identification and metabolic profiling of microalgal single cells via ensemble learning of ramanomes. Anal. Chem. 93, 8872\u20138880 (2021). https:\/\/doi.org\/10.1021\/acs.analchem.1c01015","journal-title":"Anal. Chem."},{"key":"28_CR25","doi-asserted-by":"publisher","unstructured":"Mirasbekov, Y., et al.: Semi-automated classification of colonial Microcystis by FlowCAM imaging flow cytometry in mesocosm experiment reveals high heterogeneity during seasonal bloom. Sci. Rep. 11 (2021). https:\/\/doi.org\/10.1038\/s41598-021-88661-2","DOI":"10.1038\/s41598-021-88661-2"},{"key":"28_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.marpolbul.2020.111927","volume":"163","author":"Y Wang","year":"2021","unstructured":"Wang, Y., Ju, P., Wang, S., Su, J., Zhai, W., Wu, C.: Identification of living and dead microalgae cells with digital holography and verified in the East China Sea. Mar. Pollut. Bull. 163, 111927 (2021). https:\/\/doi.org\/10.1016\/j.marpolbul.2020.111927","journal-title":"Mar. Pollut. Bull."},{"key":"28_CR27","doi-asserted-by":"publisher","unstructured":"Memmolo, P., et al.: Learning diatoms classification from a dry test slide by holographic microscopy. Sensors 20, 6353 (2020). https:\/\/doi.org\/10.3390\/s20216353","DOI":"10.3390\/s20216353"},{"key":"28_CR28","doi-asserted-by":"publisher","first-page":"30686","DOI":"10.1364\/OE.406036","volume":"28","author":"Z Xu","year":"2020","unstructured":"Xu, Z., Jiang, Y., Ji, J., Forsberg, E., Li, Y., He, S.: Classification, identification, and growth stage estimation of microalgae based on transmission hyperspectral microscopic imaging and machine learning. Opt. Express 28, 30686 (2020). https:\/\/doi.org\/10.1364\/OE.406036","journal-title":"Opt. Express"}],"container-title":["Lecture Notes in Computer Science","Information Integration and Web Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-48316-5_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T19:04:10Z","timestamp":1703703850000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-48316-5_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031483158","9783031483165"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-48316-5_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"22 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"iiWAS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Integration and Web Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Denpasar","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Indonesia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iiwas2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iiwas.org\/conferences\/iiwas2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mix","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"HotCRP","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"96","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"25% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}