التفاصيل البيبلوغرافية
| العنوان: |
Improved YOLOX-Tiny network for detection of tobacco brown spot disease |
| المؤلفون: |
Jianwu Lin, Dianzhi Yu, Renyong Pan, Jitong Cai, Jiaming Liu, Licai Zhang, Xingtian Wen, Xishun Peng, Tomislav Cernava, Safa Oufensou, Quirico Migheli, Xiaoyulong Chen, Xin Zhang |
| المصدر: |
Frontiers in Plant Science, Vol 14 (2023) |
| بيانات النشر: |
Frontiers Media S.A., 2023. |
| سنة النشر: |
2023 |
| المجموعة: |
LCC:Plant culture |
| مصطلحات موضوعية: |
object detection, tobacco brown spot disease, YOLOX-Tiny network, hierarchical mixed-scale units, convolutional block attention modules, Plant culture, SB1-1110 |
| الوصف: |
IntroductionTobacco brown spot disease caused by Alternaria fungal species is a major threat to tobacco growth and yield. Thus, accurate and rapid detection of tobacco brown spot disease is vital for disease prevention and chemical pesticide inputs.MethodsHere, we propose an improved YOLOX-Tiny network, named YOLO-Tobacco, for the detection of tobacco brown spot disease under open-field scenarios. Aiming to excavate valuable disease features and enhance the integration of different levels of features, thereby improving the ability to detect dense disease spots at different scales, we introduced hierarchical mixed-scale units (HMUs) in the neck network for information interaction and feature refinement between channels. Furthermore, in order to enhance the detection of small disease spots and the robustness of the network, we also introduced convolutional block attention modules (CBAMs) into the neck network.ResultsAs a result, the YOLO-Tobacco network achieved an average precision (AP) of 80.56% on the test set. The AP was 3.22%, 8.99%, and 12.03% higher than that obtained by the classic lightweight detection networks YOLOX-Tiny network, YOLOv5-S network, and YOLOv4-Tiny network, respectively. In addition, the YOLO-Tobacco network also had a fast detection speed of 69 frames per second (FPS).DiscussionTherefore, the YOLO-Tobacco network satisfies both the advantages of high detection accuracy and fast detection speed. It will likely have a positive impact on early monitoring, disease control, and quality assessment in diseased tobacco plants. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
1664-462X |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fpls.2023.1135105/full; https://doaj.org/toc/1664-462X |
| DOI: |
10.3389/fpls.2023.1135105 |
| URL الوصول: |
https://doaj.org/article/5bb39f5fc3bc4299ba598981b5af9dc7 |
| رقم الانضمام: |
edsdoj.5bb39f5fc3bc4299ba598981b5af9dc7 |
| قاعدة البيانات: |
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