Pollen Grain Classification Challenge 2020-Reference-Cited by-同舟云学术

Pollen Grain Classification Challenge 2020

Published:2021 Issue: Volume: Page:469-479
ISSN:0302-9743
Container-title:Pattern Recognition. ICPR International Workshops and Challenges
language:
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Author:

Battiato Sebastiano^ORCID,Guarnera Francesco^ORCID,Ortis Alessandro^ORCID,Trenta Francesca^ORCID,Ascari Lorenzo^ORCID,Siniscalco Consolata^ORCID,De Gregorio Tommaso,Suárez Eloy

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-68793-9_34

Reference34 articles.

1. Alotaibi, S.S., et al.: Pollen molecular biology: applications in the forensic palynology and future prospects: a review. Saudi J. Biol. Sci. 27(5), 1185–1190 (2020). https://doi.org/10.1016/j.sjbs.2020.02.019

2. 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

3. 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. 980–981 (2020)

4. 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. 2456–2460. IEEE (2020)

5. Buters, J.T., et al.: Pollen and spore monitoring in the world. Clin. Transl. Allergy 8(1), 1–5 (2018). https://doi.org/10.1186/s13601-018-0197-8

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