Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops RHM Condori, LM Romualdo, OM Bruno, PH de Cerqueira Luz 2017 Workshop of Computer Vision (WVC), 7-12, 2017 | 26 | 2017 |
Multilayer complex network descriptors for color–texture characterization LFS Scabini, RHM Condori, WN Gonçalves, OM Bruno Information Sciences 491, 30-47, 2019 | 24 | 2019 |
Automatic classification of physical defects in green coffee beans using CGLCM and SVM RHM Condori, JHC Humari, CE Portugal-Zambrano, ... Computing Conference (CLEI), 2014 XL Latin American, 2014 | 14 | 2014 |
Analysis of activation maps through global pooling measurements for texture classification RHM Condori, OM Bruno Information Sciences 555, 260-279, 2021 | 7 | 2021 |
Evaluating deep convolutional neural networks as texture feature extractors LFS Scabini, RHM Condori, LC Ribas, OM Bruno Image Analysis and Processing–ICIAP 2019: 20th International Conference …, 2019 | 3 | 2019 |
WVC 2017 RT Vieira, T Negri, RHM Condori, L Maria, LF Rodrigues, MC Naldi, ... | 2 | |
Color-texture classification based on spatio-spectral complex network representations LC Ribas, LFS Scabini, RHM Condori, OM Bruno Physica A: Statistical Mechanics and its Applications 635, 129518, 2024 | | 2024 |
Multi-layer analysis of convolutional neural networks for transfer learning applications RHM Condori Universidade de São Paulo, 2022 | | 2022 |
Análise de textura em imagens baseado em medidas de complexidade RHM Condori Universidade de São Paulo, 2015 | | 2015 |
Spatio-Spectral Representation Learning for Color-Texture Classification LC Ribas, LFS Scabini, RHM Condori, O Bruno Available at SSRN 4266882, 0 | | |