| Modeling yield response to crop management using convolutional neural networks A Barbosa, R Trevisan, N Hovakimyan, NF Martin Computers and Electronics in Agriculture 170, 105197, 2020 | 95 | 2020 |
| A method to obtain orange crop geometry information using a mobile terrestrial laser scanner and 3D modeling AF Colaço, RG Trevisan, JP Molin, JR Rosell-Polo, A Escolà Remote Sensing 9 (8), 763, 2017 | 80 | 2017 |
| Spatial variability of crop responses to agronomic inputs in on‑farm precision experimentation RG Trevisan, DS Bullock, NF Martin Precision Agriculture, 2020 | 62 | 2020 |
| High-throughput phenotyping of soybean maturity using time series UAV imagery and convolutional neural networks R Trevisan, O Pérez, N Schmitz, B Diers, N Martin Remote Sensing 12 (21), 3617, 2020 | 31 | 2020 |
| Orange tree canopy volume estimation by manual and LiDAR-based methods AF Colaço, RG Trevisan, JP Molin, JR Rosell-Polo, A Escolà Advances in Animal Biosciences 8 (2), 477-480, 2017 | 31 | 2017 |
| The 1st agriculture-vision challenge: Methods and results MT Chiu, X Xu, K Wang, J Hobbs, N Hovakimyan, TS Huang, H Shi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 30 | 2020 |
| Canopy sensor placement for variable-rate nitrogen application in sugarcane fields LR Amaral, RG Trevisan, JP Molin Precision agriculture 19, 147-160, 2018 | 30 | 2018 |
| Aspectos hidrológicos da recuperação florestal de áreas de preservação permanente ao longo dos corpos d’água LF Salemi, JD Groppo, R Trevisan, JM de Moraes, LA Martinelli, ... Revista do Instituto Florestal 23 (1), 69-80, 2011 | 18 | 2011 |
| Yield mapping methods for manually harvested crops AF Colaço, RG Trevisan, FHS Karp, JP Molin Computers and Electronics in Agriculture 177, 105693, 2020 | 13 | 2020 |
| Management of plant growth regulators in cotton using active crop canopy sensors RG Trevisan, NS Vilanova Junior, MT Eitelwein, JP Molin Agriculture 8 (7), 101, 2018 | 11 | 2018 |
| Use of crop height and optical sensor readings to predict mid-season cotton biomass RG Trevisan, N de SV Junior, G Portz, MT Eitelwein, JP Molin Precision agriculture'15, 103-110, 2015 | 9 | 2015 |
| Nitrogen dynamics in hydrological flow paths of a small tropical pasture catchment LF Salemi, JD Groppo, R Trevisan, SF de Barros Ferraz, JM de Moraes, ... Catena 127, 250-257, 2015 | 8 | 2015 |
| Improving yield mapping accuracy using remote sensing RG Trevisan, LS Shiratsuchi, DS Bullock, NF Martin The 12th European Conference on Precision Agriculture, 2019 | 7 | 2019 |
| Variability of physical properties of soil and rice grown under cover crops in crop-livestock integrated system RG Trevisan, OS Freddi, FJ Wruck, RR Tavanti, FSC Peres Bragantia 76, 145-154, 2017 | 7 | 2017 |
| Variabilidade de atributos físicos do solo e do arroz cultivado sob plantas de cobertura em sistema de integração lavoura-pecuária RG Trevisan, OS Freddi, FJ Wruck, RR Tavanti, FSC Peres Bragantia 76, 145-154, 2017 | 7 | 2017 |
| Measuring height of sugarcane plants through LiDAR technology TF Canata, JP Molin, AF Colaço, RG Trevisan, M Martello, PR Fiorio Proceedings of the 13th International Conference on Precision Agriculture …, 2016 | 7 | 2016 |
| Yield mapping methods for manually harvested crops AF Colaço, RG Trevisan, FHS Karp, JP Molin Precision agriculture'15, 225-232, 2015 | 7 | 2015 |
| Avaliação da precisão dos sinais RTK e RTX em ensaio estático e cinemático RG Trevisan, MT Eitelwein, NS Vilanova Jr, JV Salvi, BP Passalaqua, ... Congresso Brasileiro de Agricultura de Precisão-ConBAP. São Pedro, São Paulo, 2014 | 7 | 2014 |
| Precision Agriculture in Brazil: The Trajectory of 25 Years of Scientific Research MR Cherubin, JM Damian, TR Tavares, RG Trevisan, AF Colaço, ... Agriculture 12 (11), 1882, 2022 | 6 | 2022 |
| Site-specific treatment responses in on-farm precision experimentation RG Trevisan, DS Bullock, NF Martin The 12th European Conference on Precision Agriculture, 2019 | 6 | 2019 |
Jose Paulo MolinProfessor, Universidade de São PauloE-mail confirmado em usp.br
