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http://cio.repositorioinstitucional.mx/jspui/handle/1002/1322| RGB AND MULTISPECTRAL IMAGE ANALYSIS BASED ON DEEP LEARNING FOR REAL-TIME DETECTION AND CONTROL OF WEEDS IN CORNFIELDS | |
| Francisco Garibaldi Márquez | |
| Luis Manuel Valentín Coronado Gerardo Flores | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| Deep learning Weed detection Weed control Smart weed sprayer Reduction of herbicide usage | |
| "In this study, a vision system based on deep learning (DL) was proposed for real-time detection and control of weeds in actual corn fields. Initially, a dataset comprising RGB and multispectral images was generated and annotated at the pixel level. Subsequently, both end-to-end semantic segmentation convolutional neural networks (CNNs) and transformers were investigated. The transformer model outperformed CNNs in segmenting weeds. Utilizing this vision system, a Smart Weed Sprayer (SWS) was developed, resulting in a 45.64% reduction in herbicide usage compared to a conventional weed sprayer (CWS), while maintaining similar effectiveness in weed control." | |
| 23-04-2024 | |
| Tesis de doctorado | |
| Inglés | |
| Bibliotecarios Estudiantes Investigadores Público en general | |
| Garibaldi-Márquez, (2024). "RGB and multispectral image analysis based on deep learning for real-time detection and control of weeds in cornfields". Tesis de Doctorado Interinstitucional en Ciencia y Tecnología. Centro de Investigaciones en Óptica, A.C. Aguascalientes, Ags., México. 214 páginas. | |
| PROTECCIÓN DE LOS CULTIVOS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | DOCTORADO INTERINSTITUCIONAL EN CIENCIA Y TECNOLOGÍA (DPICYT) |
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| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| 18467.pdf | Texto completo/ Full-text available | 3.95 MB | Adobe PDF | Visualizar/Abrir |