Convolutional neural networks in predicting cotton yield from images of commercial fields. - Danilo Tedesco-Oliveira; Rouverson Pereira da Silva; Walter Maldonado Júnior; Cristiano Zerbato (Comput. Electron. Agric., 2020)

Predicting on multi-target regression for the yield of sweet potato by the market class of its roots upon vegetation indices. - Danilo Tedesco; Bruno Rafael de Almeida Moreira; Marcelo Rodrigues Barbosa Júnior; João Paulo Papa; Rouverson Pereira da Silva (Comput. Electron. Agric., 2021)

Remote Sensing on Alfalfa as an Approach to Optimize Production Outcomes: A Review of Evidence and Directions for Future Assessments. - Danilo Tedesco; Luciana Nieto; Carlos Hernández; Juan F. Rybecky; Doohong Min; Ajay Sharda; Kevin J. Hamilton; Ignacio Antonio Ciampitti (Remote. Sens., 2022)

Precision agriculture in the United States: A comprehensive meta-review inspiring further research, innovation, and adoption. - Marcelo Rodrigues Barbosa Júnior; Bruno Rafael de Almeida Moreira; Vinicius dos Santos Carreira; Armando Lopes de Brito Filho; Carolina Trentin; Flávia Luize Pereira de Souza; Danilo Tedesco; Tri Setiyono; Joao Paulo Flores 001; Yiannis Ampatzidis; Rouverson Pereira da Silva; Luciano Shozo Shiratsuchi (Comput. Electron. Agric., 2024)

Predicting below and above-ground peanut biomass and maturity using multi-target regression. - Mailson Freire de Oliveira; Franciele Morlin Carneiro; Brenda Valeska Ortiz; Megan Thurmond; Luan Pereira Oliveira; Yin Bao; Alvaro Sanz-Sáez; Danilo Tedesco (Comput. Electron. Agric., 2024)

Deep convolutional networks based on lightweight YOLOv8 to detect and estimate peanut losses from images in post-harvesting environments. - Armando Lopes de Brito Filho; Franciele Morlin Carneiro; Vinicius dos Santos Carreira; Danilo Tedesco; Jarlyson Brunno Costa Souza; Marcelo Rodrigues Barbosa Júnior; Rouverson Pereira da Silva (Comput. Electron. Agric., 2025)