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| Filter results2 paper(s) found. |
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1. Web Application Based on CNN for Classification of Biotic and Abiotic Stresses in Coffee LeavesThe use of digital systems can assist coffee growers and professionals in diagnosing stresses that affect coffee plantations, ensuring that crop management is carried out correctly and efficiently. Therefore, the aim of this study was to develop a web application based on a pre-trained Convolutional Neural Network to classify coffee leaf images exhibiting symptoms of biotic and abiotic stresses. Initially, a dataset consisting of coffee leaf images affected by biotic and abiotic stresses was constructed.... D.H. Leite, D.S. Valente, P.M. Arruda, F.D. Tancredi, D. Queiroz, G. Dumbá Monteiro De Castro |
2. Plant-Level Coffee Production Estimation Based on Morphological IndicesProduction estimation in coffee farming is traditionally conducted at aggregated spatial scales, which often limits the characterization of variability among individual plants and constrains its applicability for precision-oriented management. In production systems where within-field heterogeneity affects decisions related to harvesting, logistics, and crop management, approaches capable of representing plant-level variability become particularly relevant. Within this context, this study proposes... D. Queiroz, D.H. Leite, D. Sárvio Valente, G. Dumbá Monteiro De Castro, D.B. Marin |