Recognition and Classification of Pollen Grains Based on the Use of Statistical, Dynamic Image Characteristics, and Unique Properties of Neural Networks-Reference-Cited by-同舟云学术

Recognition and Classification of Pollen Grains Based on the Use of Statistical, Dynamic Image Characteristics, and Unique Properties of Neural Networks

Published:2021 Issue: Volume: Page:170-179
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Ibragimovich Jumanov Isroil^ORCID,Isroilovich Djumanov Olim^ORCID,Abdullayevich Safarov Rustam^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-68004-6_22

Reference11 articles.

1. Rendondo, R., Marcos V.: Pollen segmentation and feature evaluation for automatic classification in bright-field microscopy. Comput. Electron. Agric. 110, 56–69 (2017). https://www.sciencedirect.com/science/journal/01681699/

2. Chica, M.: Standard methods for inexpensive pollen loads authentication by means of computer vision and machine learning. https://www.arxiv.org/ftp/arxiv/papers/1511/1511.04320.pdf (2017)

3. Chica, M., Campoy, P.: Discernment of bee pollen loads using computer vision and oneclass classification techniques. J. Food Eng. 112, 50–59 (2012)

4. Xanjina, N.Y., Zamyatina, Y.B.: Ispolzovaniye klassicheskix metodov i neyronnix setey dlya raspoznavaniya pilsevix zeren.Vestnik Permskogo universiteta. Matematika. Mexanika. Informatika. 4(23), 111–119 (2013)

5. Chernix, A.S., Zamyatina, Y.B.: Issledovaniye vozmojnosti primeneniya ryada klassicheskix metodov dlya raspoznavaniya pilsevix zeren. Perm: Izd-vo Perm. gos. nas. issled. un-ta, (2012)

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