| Full text | |
| Author(s): |
Tetila, Everton Castelao
;
da Silveira, Fabio Amaral Godoy
;
Costa, Anderson Bessa da
;
Amorim, Willian Paraguassu
;
Astolfi, Gilberto
;
Pistori, Hemerson
;
Barbedo, Jayme Garcia Arnal
Total Authors: 7
|
| Document type: | Journal article |
| Source: | SMART AGRICULTURAL TECHNOLOGY; v. 7, p. 10-pg., 2024-02-05. |
| Abstract | |
In this work, we evaluated the You Only Look Once (YOLO) architecture for real-time detection of soybean pests. We collected images of the soybean plantation in different days, locations and weather conditions, between the phenological stages R1 to R6, which have a high occurrence of insect pests in soybean fields. We employed a 5 -fold cross -validation paired with four metrics to evaluate the classification performance and three metrics to evaluate the detection performance. Experimental results showed that YOLOv3 architecture trained with a batch size of 32 leads to higher classification and detection rates compared to batch sizes of 4 and 16. The results indicate that the evaluated architecture can support specialists and farmers in monitoring the need for pest control action in soybean fields. (AU) | |
| FAPESP's process: | 23/03870-8 - Cattle monitoring using drone images. |
| Grantee: | Everton Castelão Tetila |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 22/09319-9 - Center of Science for Development in Digital Agriculture - CCD-AD/SemeAr |
| Grantee: | Silvia Maria Fonseca Silveira Massruhá |
| Support Opportunities: | Research Grants - Science Centers for Development |