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Plant Parasitic Nematode Identification in Complex Samples with Deep Learning

Sahil Agarwal

Sahil Agarwal

Department of Electrical & Computer Engineering, University of FloridaGainesville,
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Agarwal, Sahil
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Zachary C. Curran

Zachary C. Curran

Department of Computer & Information Science and Engineering, University of FloridaGainesville,
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Curran, Zachary C.
, 
Guohao Yu

Guohao Yu

Department of Electrical & Computer Engineering, University of FloridaGainesville,
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Yu, Guohao
, 
Shova Mishra

Shova Mishra

Department of Entomology and Nematology, University of FloridaGainesville,
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Mishra, Shova
, 
Anil Baniya

Anil Baniya

Department of Entomology and Nematology, University of FloridaGainesville,
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Baniya, Anil
, 
Mesfin Bogale

Mesfin Bogale

Department of Entomology and Nematology, University of FloridaGainesville,
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Bogale, Mesfin
, 
Kody Hughes

Kody Hughes

Department of Entomology and Nematology, University of FloridaGainesville,
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Hughes, Kody
, 
Oscar Salichs

Oscar Salichs

Department of Entomology and Nematology, University of FloridaGainesville,
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Salichs, Oscar
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Alina Zare

Alina Zare

Department of Electrical & Computer Engineering, University of FloridaGainesville,
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Zare, Alina
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Zhe Jiang

Zhe Jiang

Department of Computer & Information Science and Engineering, University of FloridaGainesville,
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Jiang, Zhe
 oraz 
Peter DiGennaro

Peter DiGennaro

Department of Entomology and Nematology, University of FloridaGainesville,
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DiGennaro, Peter
  
16 paź 2023
Plant Parasitic Nematode Identification in Complex Samples with Deep Learning's Cover Image
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Kategoria artykułu: Research Note
Data publikacji: 16 paź 2023
Otrzymano: 07 lip 2023
DOI: https://doi.org/10.2478/jofnem-2023-0045
Słowa kluczowe
© 2023 Sahil Agarwal et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1:

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

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

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
Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne
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