{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T19:48:00Z","timestamp":1775245680309,"version":"3.50.1"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030012366","type":"print"},{"value":"9783030012373","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01237-3_31","type":"book-chapter","created":{"date-parts":[[2018,10,6]],"date-time":"2018-10-06T14:42:18Z","timestamp":1538836938000},"page":"511-526","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Coded Illumination and Imaging for Fluorescence Based Classification"],"prefix":"10.1007","author":[{"given":"Yuta","family":"Asano","sequence":"first","affiliation":[]},{"given":"Misaki","family":"Meguro","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Antony","family":"Lam","sequence":"additional","affiliation":[]},{"given":"Yinqiang","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Takahiro","family":"Okabe","sequence":"additional","affiliation":[]},{"given":"Imari","family":"Sato","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,10,7]]},"reference":[{"key":"31_CR1","doi-asserted-by":"crossref","unstructured":"Gu, J., Liu, C.: Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 797\u2013804, June 2012","DOI":"10.1109\/CVPR.2012.6247751"},{"issue":"1","key":"31_CR2","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1109\/TPAMI.2013.110","volume":"36","author":"C Liu","year":"2014","unstructured":"Liu, C., Gu, J.: Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 36(1), 86\u201398 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"},{"key":"31_CR3","doi-asserted-by":"crossref","unstructured":"Wang, C., Okabe, T.: Joint optimization of coded illumination and grayscale conversion for one-shot raw material classification. In: British Machine Vision Conference (BMVC) (2017)","DOI":"10.5244\/C.31.136"},{"key":"31_CR4","doi-asserted-by":"crossref","unstructured":"Blasinski, H., Farrell, J., Wandell, B.: Designing illuminant spectral power distributions for surface classification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017","DOI":"10.1109\/CVPR.2017.287"},{"key":"31_CR5","doi-asserted-by":"crossref","unstructured":"Sugiyama, J., Fujita, K., Yoshimura, M., Tsuta, M., Shibata, M., Kokawa, M.: Detection of food hazards using fluorescence fingerprint. IFAC Proc. Vol. 46(18), 70\u201374 (2013). 4th IFAC Conference on Modelling and Control in Agriculture, Horticulture and Post Harvest Industry","DOI":"10.3182\/20130828-2-SF-3019.00035"},{"issue":"2","key":"31_CR6","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1016\/j.foodchem.2005.09.082","volume":"100","author":"R Karoui","year":"2007","unstructured":"Karoui, R., Dufour, E., Schoonheydt, R., Baerdemaeker, J.D.: Characterisation of soft cheese by front face fluorescence spectroscopy coupled with chemometric tools: effect of the manufacturing process and sampling zone. Food Chem. 100(2), 632\u2013642 (2007)","journal-title":"Food Chem."},{"issue":"16","key":"31_CR7","doi-asserted-by":"publisher","first-page":"6785","DOI":"10.1021\/jf800117k","volume":"56","author":"David Chabreyrie","year":"2008","unstructured":"Chabreyrie, D., Chauvet, S., Guyon, F.: Salagoty M.H., Antinelli, J.F., Medina, B.: Characterization and quantification of grape variety by means of shikimic acid concentration and protein fingerprint in still white wines. J. Agric. Food Chem. 56(16), 6785\u20136790 (2008). PMID: 18624410","journal-title":"Journal of Agricultural and Food Chemistry"},{"issue":"5","key":"31_CR8","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1016\/S0963-9969(02)00174-6","volume":"36","author":"E Dufour","year":"2003","unstructured":"Dufour, E., Frencia, J.P., Kane, E.: Development of a rapid method based on front-face fluorescence spectroscopy for the monitoring of fish freshness. Food Res. Int. 36(5), 415\u2013423 (2003)","journal-title":"Food Res. Int."},{"issue":"5","key":"31_CR9","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1366\/13-07325","volume":"68","author":"L Lenhardt","year":"2014","unstructured":"Lenhardt, L., Zekovic, I., Dramicanin, T., Dramicanin, M.D., Bro, R.: Determination of the botanical origin of honey by front-face synchronous fluorescence spectroscopy. Appl. Spectrosc. 68(5), 557\u2013563 (2014)","journal-title":"Appl. Spectrosc."},{"key":"31_CR10","doi-asserted-by":"crossref","unstructured":"Lam, A., Sato, I.: Spectral modeling and relighting of reflective-fluorescent scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1452\u20131459, June 2013","DOI":"10.1109\/CVPR.2013.191"},{"issue":"5","key":"31_CR11","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/TPAMI.2015.2473839","volume":"38","author":"Y Fu","year":"2016","unstructured":"Fu, Y., Lam, A., Sato, I., Okabe, T., Sato, Y.: Separating reflective and fluorescent components using high frequency illumination in the spectral domain. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 38(5), 965\u2013978 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"},{"issue":"7","key":"31_CR12","doi-asserted-by":"publisher","first-page":"1313","DOI":"10.1109\/TPAMI.2015.2439270","volume":"38","author":"Y Fu","year":"2016","unstructured":"Fu, Y., Lam, A., Sato, I., Okabe, T., Sato, Y.: Reflectance and fluorescence spectral recovery via actively lit RGB images. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 38(7), 1313\u20131326 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"},{"key":"31_CR13","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Fu, Y., Lam, A., Sato, I., Sato, Y.: Separating fluorescent and reflective components by using a single hyperspectral image. In: IEEE International Conference on Computer Vision (ICCV), pp. 3523\u20133531, December 2015","DOI":"10.1109\/ICCV.2015.402"},{"issue":"3","key":"31_CR14","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01237-3_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T18:48:37Z","timestamp":1775242117000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01237-3_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012366","9783030012373"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01237-3_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"7 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}