{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T02:21:24Z","timestamp":1767666084186,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030687922"},{"type":"electronic","value":"9783030687939"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-68793-9_34","type":"book-chapter","created":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T16:28:24Z","timestamp":1613838504000},"page":"469-479","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Pollen Grain Classification Challenge 2020"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6127-2470","authenticated-orcid":false,"given":"Sebastiano","family":"Battiato","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7703-3367","authenticated-orcid":false,"given":"Francesco","family":"Guarnera","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3461-4679","authenticated-orcid":false,"given":"Alessandro","family":"Ortis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2524-3837","authenticated-orcid":false,"given":"Francesca","family":"Trenta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5549-2124","authenticated-orcid":false,"given":"Lorenzo","family":"Ascari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-4980","authenticated-orcid":false,"given":"Consolata","family":"Siniscalco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tommaso","family":"De Gregorio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eloy","family":"Su\u00e1rez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,21]]},"reference":[{"issue":"5","key":"34_CR1","doi-asserted-by":"publisher","first-page":"1185","DOI":"10.1016\/j.sjbs.2020.02.019","volume":"27","author":"SS Alotaibi","year":"2020","unstructured":"Alotaibi, S.S., et al.: Pollen molecular biology: applications in the forensic palynology and future prospects: a review. Saudi J. Biol. Sci. 27(5), 1185\u20131190 (2020). https:\/\/doi.org\/10.1016\/j.sjbs.2020.02.019","journal-title":"Saudi J. Biol. Sci."},{"key":"34_CR2","doi-asserted-by":"publisher","first-page":"101165","DOI":"10.1016\/j.ecoinf.2020.101165","volume":"60","author":"G Astolfi","year":"2020","unstructured":"Astolfi, G., et al.: POLLEN73S: an image dataset for pollen grains classification. Ecol. Inf. 60, 101165 (2020). https:\/\/doi.org\/10.1016\/j.ecoinf.2020.101165","journal-title":"Ecol. Inf."},{"key":"34_CR3","doi-asserted-by":"crossref","unstructured":"Battiato, S., Ortis, A., Trenta, F., Ascari, L., Politi, M., Siniscalco, C.: Detection and classification of pollen grain microscope images. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 980\u2013981 (2020)","DOI":"10.1109\/CVPRW50498.2020.00498"},{"key":"34_CR4","doi-asserted-by":"crossref","unstructured":"Battiato, S., Ortis, A., Trenta, F., Ascari, L., Politi, M., Siniscalco, C.: Pollen13k: a large scale microscope pollen grain image dataset. In: IEEE International Conference on Image Processing (ICIP), pp. 2456\u20132460. IEEE (2020)","DOI":"10.1109\/ICIP40778.2020.9190776"},{"key":"34_CR5","doi-asserted-by":"publisher","unstructured":"Buters, J.T., et al.: Pollen and spore monitoring in the world. Clin. Transl. Allergy 8(1), 1\u20135 (2018). https:\/\/doi.org\/10.1186\/s13601-018-0197-8","DOI":"10.1186\/s13601-018-0197-8"},{"issue":"1","key":"34_CR6","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1159\/000355630","volume":"163","author":"D Caillaud","year":"2014","unstructured":"Caillaud, D., Martin, S., Segala, C., Besancenot, J.P., Clot, B., Thibaudon, M.: Effects of airborne birch pollen levels on clinical symptoms of seasonal allergic rhinoconjunctivitis. Int. Arch. Allergy Immunol. 163(1), 43\u201350 (2014). https:\/\/doi.org\/10.1159\/000355630","journal-title":"Int. Arch. Allergy Immunol."},{"key":"34_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Y., Bai, Y., Zhang, W., Mei, T.: Destruction and construction learning for fine-grained image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5157\u20135166 (2019)","DOI":"10.1109\/CVPR.2019.00530"},{"key":"34_CR8","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.atmosenv.2016.05.062","volume":"140","author":"B Crouzy","year":"2016","unstructured":"Crouzy, B., Stella, M., Konzelmann, T., Calpini, B., Clot, B.: All-optical automatic pollen identification: towards an operational system. Atmos. Environ. 140, 202\u2013212 (2016). https:\/\/doi.org\/10.1016\/j.atmosenv.2016.05.062","journal-title":"Atmos. Environ."},{"key":"34_CR9","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.eja.2015.10.008","volume":"73","author":"M Cunha","year":"2016","unstructured":"Cunha, M., Ribeiro, H., Abreu, I.: Pollen-based predictive modelling of wine production: application to an arid region. Eur. J. Agron. 73, 42\u201354 (2016). https:\/\/doi.org\/10.1016\/j.eja.2015.10.008","journal-title":"Eur. J. Agron."},{"key":"34_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/978-3-319-50835-1_30","volume-title":"Advances in Visual Computing","author":"A Daood","year":"2016","unstructured":"Daood, A., Ribeiro, E., Bush, M.: Pollen grain recognition using deep learning. In: Bebis, G., et al. (eds.) ISVC 2016. LNCS, vol. 10072, pp. 321\u2013330. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-50835-1_30"},{"key":"34_CR11","first-page":"4","volume":"89","author":"A Duller","year":"1999","unstructured":"Duller, A., Guller, G., France, I., Lamb, H.: A pollen image database for evaluation of automated identification systems. Quat. Newsl. 89, 4\u20139 (1999)","journal-title":"Quat. Newsl."},{"key":"34_CR12","doi-asserted-by":"crossref","unstructured":"Fang, J., Sun, Y., Zhang, Q., Li, Y., Liu, W., Wang, X.: Densely connected search space for more flexible neural architecture search. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10628\u201310637 (2020)","DOI":"10.1109\/CVPR42600.2020.01064"},{"issue":"2","key":"34_CR13","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/s10453-013-9320-4","volume":"30","author":"\u00c1 Fern\u00e1ndez-Llamazares","year":"2013","unstructured":"Fern\u00e1ndez-Llamazares, \u00c1., Belmonte, J., Boada, M., Fraixedas, S.: Airborne pollen records and their potential applications to the conservation of biodiversity. Aerobiologia 30(2), 111\u2013122 (2013). https:\/\/doi.org\/10.1007\/s10453-013-9320-4","journal-title":"Aerobiologia"},{"issue":"6","key":"34_CR14","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1016\/S0277-3791(99)00021-9","volume":"19","author":"I France","year":"2000","unstructured":"France, I., Duller, A.W., Duller, G.A., Lamb, H.F.: A new approach to automated pollen analysis. Quat. Sci. Rev. 19(6), 537\u2013546 (2000). https:\/\/doi.org\/10.1016\/S0277-3791(99)00021-9","journal-title":"Quat. Sci. Rev."},{"issue":"16","key":"34_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s19163583","volume":"19","author":"R Gallardo-Caballero","year":"2019","unstructured":"Gallardo-Caballero, R., Garc\u00eda-Orellana, C.J., Garc\u00eda-Manso, A., Gonz\u00e1lez-Velasco, H.M., Tormo-Molina, R., Mac\u00edas-Mac\u00edas, M.: Precise pollen grain detection in bright field microscopy using deep learning techniques. Sensors (Switzerland) 19(16), 1\u201319 (2019). https:\/\/doi.org\/10.3390\/s19163583","journal-title":"Sensors (Switzerland)"},{"issue":"6","key":"34_CR16","doi-asserted-by":"publisher","first-page":"e0157044","DOI":"10.1371\/journal.pone.0157044","volume":"11","author":"AB Goncalves","year":"2016","unstructured":"Goncalves, A.B., et al.: Feature extraction and machine learning for the classification of Brazilian savannah pollen grains. PLoS ONE 11(6), e0157044 (2016). https:\/\/doi.org\/10.1371\/journal.pone.0157044","journal-title":"PLoS ONE"},{"issue":"17","key":"34_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1128\/AEM.00809-17","volume":"83","author":"AE Haddrell","year":"2017","unstructured":"Haddrell, A.E., Thomas, R.J.: Aerobiology: experimental considerations, observations, and future tools. Appl. Environ. Microbiol. 83(17), 1\u201315 (2017). https:\/\/doi.org\/10.1128\/AEM.00809-17","journal-title":"Appl. Environ. Microbiol."},{"issue":"11","key":"34_CR18","doi-asserted-by":"publisher","first-page":"5433","DOI":"10.5194\/acp-14-5433-2014","volume":"14","author":"JD Hader","year":"2014","unstructured":"Hader, J.D., Wright, T.P., Petters, M.D.: Contribution of pollen to atmospheric ice nuclei concentrations. Atmos. Chem. Phys. 14(11), 5433\u20135449 (2014). https:\/\/doi.org\/10.5194\/acp-14-5433-2014","journal-title":"Atmos. Chem. Phys."},{"key":"34_CR19","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"3","key":"34_CR20","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1111\/nph.12848","volume":"203","author":"KA Holt","year":"2014","unstructured":"Holt, K.A., Bennett, K.: Principles and methods for automated palynology. New Phytol. 203(3), 735\u2013742 (2014). https:\/\/doi.org\/10.1111\/nph.12848","journal-title":"New Phytol."},{"issue":"5","key":"34_CR21","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1080\/02786826.2019.1664724","volume":"54","author":"JA Huffman","year":"2020","unstructured":"Huffman, J.A., et al.: Real-time sensing of bioaerosols: review and current perspectives. Aerosol Sci. Technol. 54(5), 465\u2013495 (2020). https:\/\/doi.org\/10.1080\/02786826.2019.1664724","journal-title":"Aerosol Sci. Technol."},{"issue":"5","key":"34_CR22","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1111\/j.1365-3059.2011.02445.x","volume":"60","author":"SL Jackson","year":"2011","unstructured":"Jackson, S.L., Bayliss, K.L.: Spore traps need improvement to fulfil plant biosecurity requirements. Plant Pathol. 60(5), 801\u2013810 (2011). https:\/\/doi.org\/10.1111\/j.1365-3059.2011.02445.x","journal-title":"Plant Pathol."},{"key":"34_CR23","doi-asserted-by":"publisher","unstructured":"Korobeynikov, A., Kamalova, Y., Palabugin, M., Basov, I.: The use of convolutional neural network LeNet for pollen grains classification. In: \u201cInstrumentation Engineering, Electronics and Telecommunications\" Proceedings of the IV International Forum, Izhevsk, Russia, pp. 38\u201344 (2018). https:\/\/doi.org\/10.22213\/2658-3658-2018-38-44","DOI":"10.22213\/2658-3658-2018-38-44"},{"key":"34_CR24","unstructured":"Li, P., Flenley, J., Empson, L.K.: Classification of 13 types of New Zealand pollen patterns using neural networks. In: IVCNZ (1998)"},{"issue":"3","key":"34_CR25","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1007\/s10453-015-9367-5","volume":"31","author":"AM Mercuri","year":"2015","unstructured":"Mercuri, A.M.: Applied palynology as a trans-disciplinary science: the contribution of aerobiology data to forensic and palaeoenvironmental issues. Aerobiologia 31(3), 323\u2013339 (2015). https:\/\/doi.org\/10.1007\/s10453-015-9367-5","journal-title":"Aerobiologia"},{"key":"34_CR26","doi-asserted-by":"publisher","first-page":"16","DOI":"10.3389\/fmicb.2016.00016","volume":"7","author":"DA Pearce","year":"2016","unstructured":"Pearce, D.A., et al.: Aerobiology over Antarctica-a new initiative for atmospheric ecology. Front. Microbiol. 7, 16 (2016). https:\/\/doi.org\/10.3389\/fmicb.2016.00016","journal-title":"Front. Microbiol."},{"issue":"1","key":"34_CR27","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.patrec.2006.06.010","volume":"28","author":"M Ranzato","year":"2007","unstructured":"Ranzato, M., Taylor, P.E., House, J.M., Flagan, R.C., LeCun, Y., Perona, P.: Automatic recognition of biological particles in microscopic images. Pattern Recogn. Lett. 28(1), 31\u201339 (2007). https:\/\/doi.org\/10.1016\/j.patrec.2006.06.010","journal-title":"Pattern Recogn. Lett."},{"issue":"December","key":"34_CR28","doi-asserted-by":"publisher","first-page":"163","DOI":"10.3389\/fcimb.2012.00163","volume":"2","author":"CJ Roy","year":"2012","unstructured":"Roy, C.J., Reed, D.S.: Infectious disease aerobiology: miasma incarnate. Front. Cell. Infect. Microbiol. 2(December), 163 (2012). https:\/\/doi.org\/10.3389\/fcimb.2012.00163","journal-title":"Front. Cell. Infect. Microbiol."},{"issue":"3","key":"34_CR29","doi-asserted-by":"publisher","first-page":"1539","DOI":"10.5194\/amt-13-1539-2020","volume":"13","author":"E Sauvageat","year":"2020","unstructured":"Sauvageat, E., et al.: Real-time pollen monitoring using digital holography. Atmos. Meas. Tech. 13(3), 1539\u20131550 (2020). https:\/\/doi.org\/10.5194\/amt-13-1539-2020","journal-title":"Atmos. Meas. Tech."},{"issue":"9","key":"34_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0201807","volume":"13","author":"V Sevillano","year":"2018","unstructured":"Sevillano, V., Aznarte, J.L.: Improving classification of pollen grain images of the POLEN23E dataset through three different applications of deep learning convolutional neural networks. PLoS ONE 13(9), 1\u201318 (2018). https:\/\/doi.org\/10.1371\/journal.pone.0201807","journal-title":"PLoS ONE"},{"key":"34_CR31","doi-asserted-by":"crossref","unstructured":"Wang, Y., Morariu, V.I., Davis, L.S.: Learning a discriminative filter bank within a CNN for fine-grained recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4148\u20134157 (2018)","DOI":"10.1109\/CVPR.2018.00436"},{"issue":"1","key":"34_CR32","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1111\/aab.12191","volume":"166","author":"JS West","year":"2015","unstructured":"West, J.S., Kimber, R.: Innovations in air sampling to detect plant pathogens. Ann. Appl. Biol. 166(1), 4\u201317 (2015). https:\/\/doi.org\/10.1111\/aab.12191","journal-title":"Ann. Appl. Biol."},{"issue":"9","key":"34_CR33","doi-asserted-by":"publisher","first-page":"e17046","DOI":"10.1038\/lsa.2017.46","volume":"6","author":"YC Wu","year":"2017","unstructured":"Wu, Y.C., et al.: Air quality monitoring using mobile microscopy and machine learning. Light Sci. Appl. 6(9), e17046 (2017). https:\/\/doi.org\/10.1038\/lsa.2017.46","journal-title":"Light Sci. Appl."},{"key":"34_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1007\/978-3-030-01270-0_35","volume-title":"Computer Vision \u2013 ECCV 2018","author":"C Yu","year":"2018","unstructured":"Yu, C., Zhao, X., Zheng, Q., Zhang, P., You, X.: Hierarchical bilinear pooling for fine-grained visual recognition. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11220, pp. 595\u2013610. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01270-0_35"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. ICPR International Workshops and Challenges"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-68793-9_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T17:15:09Z","timestamp":1613841309000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-68793-9_34"}},"subtitle":["Challenge Report"],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030687922","9783030687939"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-68793-9_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"21 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ICPR2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icpr2020.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}