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Plant Parasitic Nematode Identification in Complex Samples with Deep Learning Cover

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Plant Parasitic Nematode Identification in Complex Samples with Deep Learning

Journal of Nematology

Volume 55 (2023): Issue 1 (February 2023)

By: Sahil Agarwal, Zachary C. Curran, Guohao Yu, Shova Mishra, Anil Baniya, Mesfin Bogale, Kody Hughes, Oscar Salichs, Alina Zare, Zhe Jiang and Peter DiGennaro

Open Access

|Oct 2023

Figures & tables

Figures & Tables

Representative sample image of nematodes extracted from soil samples sent to NDL. Colored boxes indicate annotations of plant parasitic nematode heads.

Table 1.

Model and corresponding maximum mAP.

Model	Max MAP_0.5
YOLOv5x Baseline	0.787
CenterNet HourGlass104 512×512	0.6929
EfficientDet D1 640×640	0.6489
SSD ResNet50 V1 FPN 640×640	0.6439

Table 2.

Modified YOLOv5 models with precision and recall.

Model	Max MAP_0.5	Max Precision	Max Recall
YOLOv5x Baseline	0.787	0.836	0.772
YOLOv5x-Bi-FPN	0.791	0.851	0.753
YOLO-v5x Densenet	0.769	0.831	0.782
YOLOv5x-Deeper	0.779	0.831	0.774

Articles in this issue

DOI: https://doi.org/10.2478/jofnem-2023-0045 | Journal eISSN: 2640-396X | Journal ISSN: 0022-300X

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Language: English

Submitted on: Jul 7, 2023

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Published on: Oct 16, 2023

Published by: Society of Nematologists, Inc.

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

identification,

Related subjects:

Life sciences, other

© 2023 Sahil Agarwal, Zachary C. Curran, Guohao Yu, Shova Mishra, Anil Baniya, Mesfin Bogale, Kody Hughes, Oscar Salichs, Alina Zare, Zhe Jiang, Peter DiGennaro, published by Society of Nematologists, Inc.
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 55 (2023): Issue 1 (February 2023)

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