2 citations · 5 across the 3 of their papers we have counts for
7 papers
A Comprehensive Modeling Approach for Crop Yield Forecasts using AI-based Methods and Crop Simulation Models
Renato Luiz de Freitas Cunha, Bruno Silva, Priscilla Barreira Avegliano
Numerous solutions for yield estimation are either based on data-driven models, or on crop-simulation models (CSMs). Researchers tend to build data-driven models using nationwide c…
Predicting Account Receivables with Machine Learning
Ana Paula Appel, Gabriel Louzada Malfatti, Renato Luiz de Freitas Cunha +2
Being able to predict when invoices will be paid is valuable in multiple industries and supports decision-making processes in most financial workflows. However, due to the complexi…
Estimating crop yields with remote sensing and deep learning
Renato Luiz de Freitas Cunha, Bruno Silva
Increasing the accuracy of crop yield estimates may allow improvements in the whole crop production chain, allowing farmers to better plan for harvest, and for insurers to better u…
DeepDownscale: a Deep Learning Strategy for High-Resolution Weather Forecast
Eduardo R. Rodrigues, Igor Oliveira, Renato L. F. Cunha +1
Running high-resolution physical models is computationally expensive and essential for many disciplines. Agriculture, transportation, and energy are sectors that depend on high-res…
An argument in favor of strong scaling for deep neural networks with small datasets
Renato L. de F. Cunha, Eduardo R. Rodrigues, Matheus Palhares Viana +1
In recent years, with the popularization of deep learning frameworks and large datasets, researchers have started parallelizing their models in order to train faster. This is cruci…
A Scalable Machine Learning System for Pre-Season Agriculture Yield Forecast
Igor Oliveira, Renato L. F. Cunha, Bruno Silva +1
Yield forecast is essential to agriculture stakeholders and can be obtained with the use of machine learning models and data coming from multiple sources. Most solutions for yield…