Species-level microfossil identification for globotruncana genus using hybrid deep learning algorithms from the scratch via a low-cost light microscope imaging-Reference-Cited by-同舟云学术

Species-level microfossil identification for globotruncana genus using hybrid deep learning algorithms from the scratch via a low-cost light microscope imaging

Published:2022-09-28 Issue:9 Volume:82 Page:13689-13718
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Ozer Ilyas,Ozer Caner Kaya,Karaca Ali Can,Gorur Kutlucan,Kocak Ismail,Cetin Onursal^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-022-13810-2.pdf

Reference69 articles.

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2. Ali A, Zhu Y, Zakarya M (2021) A data aggregation based approach to exploit dynamic spatio-temporal correlations for citywide crowd flows prediction in fog computing. Multimed Tools Appl 80:31401–31433. https://doi.org/10.1007/s11042-020-10486-4

3. Anderson TI, Vega B, Kovscek AR (2020) Multimodal imaging and machine learning to enhance microscope images of shale. Comput Geosci 145:104593. https://doi.org/10.1016/j.cageo.2020.104593

4. Bhadoria R (2019) The biometric computing: recognition and registration. CRC Press

5. Bolli HM (1957) The genera Praeglobotruncana, Rotalipora, Globotruncana and Abathomphalus in the upper Cretaceous of Trinidad, BWI. US Natl Museum Bull 215:51–60

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