A reliable and low-cost deep learning model integrating convolutional neural network and transformer structure for fine-grained classification of chicken Eimeria species-Reference-Cited by-同舟云学术

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A reliable and low-cost deep learning model integrating convolutional neural network and transformer structure for fine-grained classification of chicken Eimeria species

Published:2023-03 Issue:3 Volume:102 Page:102459
ISSN:0032-5791
Container-title:Poultry Science
language:en
Short-container-title:Poultry Science

Author:

He Pengguang^ORCID,Chen Zhonghao,He Yefan,Chen Jintian,Hayat Khawar,Pan Jinming^ORCID,Lin Hongjian^ORCID

Publisher

Elsevier BV

Subject

Animal Science and Zoology,General Medicine

Reference41 articles.

1. NemaNet: a convolutional neural network model for identification of soybean nematodes;Abade;Biosyst. Eng.,2022

2. Recognition of protozoan parasites from microscopic images: Eimeria species in chickens and rabbits as a case study;Abdalla,2017

3. Quantifying attention flow in transformers;Abnar,2020

4. A flow cytometric method for enumeration and speciation of coccidia affecting broiler chickens;Adams;Vet. Parasitol.,2022

5. Re-calculating the cost of coccidiosis in chickens;Blake;Vet. Res.,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automated Image Analysis for Detection of Coccidia in Poultry;Animals;2024-01-09

2. Amplicon sequencing allows differential quantification of closely related parasite species: an example from rodent Coccidia (Eimeria);Parasites & Vectors;2023-06-17

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