Proceedings
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| Filter results2 paper(s) found. |
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1. Influence of the Type of ANN Algorithm on Prediction of Georeferenced Sugarcane QualityOptimizing crop quality and yield is critical to the development of more sustainable agriculture on large scale. Predictive models can provide assessment of those attributes prior to harvesting using techniques of artificial intelligence to support site-specific management. The objective was to investigate the influence of ANN (Artificial Neural Network) algorithms on prediction of sugarcane quality. Brix content of sugarcane, variety CTC 2994 on second ratoon, was measured in laboratory using... T. Canata, F.P. Monachesi, O.D. Salomão, L. Rodrigues , L.E. Zonfrilli, H.C. De La Cruz, P.F. De Mello |
2. Evaluation of the Performance of Computer Vision Models in the Detection and Counting of Tomato Plants Infected by Tomato Spotted Wilt Virus (TSWV)Tomato is one of the most economically important vegetable crops worldwide. However, this crop is severely affected by Tomato Spotted Wilt Virus (TSWV), whose transmission occurs mainly through thrips. Thus, identifying infected plants is an important step to reduce the dissemination and infection of healthy plants, reducing economic losses. Computer vision-based models have been widely used in the automated detection of plant diseases. In this context, this work aimed to evaluate the performance... L.S. Souza Pinto, S. . Azevedo, M. . Medeiros, A. Felipe Dos Santos, T. Costa Barboza, M.C. Arnosti, G. Valdes Fernandez , G. Lacerda Da Silveira |