| Ship detection using TerraSAR-X images in the Campos Basin (Brazil) RL Paes, JA Lorenzzetti, DFM Gherardi IEEE Geoscience and Remote Sensing Letters 7 (3), 545-548, 2010 | 75 | 2010 |
| Single-look complex COSMO-SkyMed SAR data to observe metallic targets at sea M Migliaccio, F Nunziata, A Montuori, RL Paes IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2012 | 45 | 2012 |
| Oil rig recognition using convolutional neural network on Sentinel-1 SAR images LE Falqueto, JAS Sá, RL Paes, A Passaro IEEE Geoscience and Remote Sensing Letters 16 (8), 1329-1333, 2019 | 28 | 2019 |
| On the capability of hybrid-polarity features to observe metallic targets at sea RL Paes, F Nunziata, M Migliaccio IEEE Journal of Oceanic Engineering 41 (2), 346-361, 2015 | 25 | 2015 |
| Coastline extraction and coastal area classification via SAR hybrid-polarimetry architecture RL Paes, F Nunziata, M Migliaccio 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2015 | 14 | 2015 |
| The 2019 northeast Brazil oil spill: scenarios P Nobre, AT Lemos, E Giarolla, R Camayo, L Namikawa, M Kampel, ... Anais da Academia Brasileira de Ciências 94 (suppl 2), e20210391, 2022 | 10 | 2022 |
| A performance comparison of a CFAR ship detection algorithm using EnviSat, RadarSat, COSMO-SkyMed and Terra SAR-X images JA Lorenzzetti, RL Paes, DM Gheradi SeaSAR 2010 679, 32, 2010 | 10 | 2010 |
| Marine environmental impact on CFAR ship detection as measured by wave age in SAR images DX Bezerra, JA Lorenzzetti, RL Paes Remote Sensing 15 (13), 3441, 2023 | 9 | 2023 |
| COSMO-SkyMed SAR data to observe small metallic objects from ocean crashed aircraft RL Paes, F Nunziata, EH Shiguemori, M Migliaccio, A Montuori 2011 IEEE International Geoscience and Remote Sensing Symposium, 2869-2872, 2011 | 4 | 2011 |
| Scenario analysis as a decision-support tool: a maritime patrol case study AN Costa, RL Paes, M Zawadzki, D Geraldo Aplicações Operacionais em Áreas de Defesa 22, 30-34, 2021 | 3 | 2021 |
| Remote sensing of the oceans: Blue economy and marine pollution A Buono, RL Paes, Y Li MDPI-Multidisciplinary Digital Publishing Institute, 2021 | 3 | 2021 |
| Ship detection in the Brazilian coast using TerraSAR-X SAR images RL Paes, JA Lorenzzetti, DFM Gherardi 2009 IEEE International Geoscience and Remote Sensing Symposium 4, IV-983-IV-986, 2009 | 3 | 2009 |
| Patrulha marítima apoiada por técnicas de extração de informações de dados de satélites RL Paes, JA Lorenzzetti, DFM Gherardi Simpósio de Guerra Eletrônica (SIGE), São José dos Campos, 2006 | 3 | 2006 |
| Persistência da aplicabilidade de informações de imagens SAR orbitais em missões aéreas de vigilância e reconhecimento: uma análise por meio de simulação Monte Carlo LE Falqueto, AN Costa, D Geraldo, RL Paes Aplicações Operacionais em Áreas de Defesa 23 (1), 2022 | 2 | 2022 |
| A importância de dados polarimétricos para detecção de alvos artificiais no mar utilizando imagens SAR LE Falqueto, RL Paes, A Passaro Aplicações Operacionais em Áreas de Defesa 22, 53-58, 2021 | 2 | 2021 |
| Editorial for the special issue “Remote sensing of the oceans: blue economy and marine pollution” A Buono, Y Li, RL Paes Remote Sensing 13 (8), 1522, 2021 | 2 | 2021 |
| On the sensitivity analysis of the Compact-Polarimetry SAR architectures for maritime targets detection RL Paes, A Buono, F Nunziata, M Migliaccio Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water …, 2014 | 2 | 2014 |
| Cosmo-Skymed SAR data for urgency situations-study of a real case RL Paes, EH Shiguemori, M Habermann, AMR Neto, RM Andrade Computational Vision and Medical Image Processing: VipIMAGE 2011, 329, 2011 | 2 | 2011 |
| Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data RL Paes, A Pagamisse Convergence and Hybrid Information Technology: 5th International Conference …, 2011 | 2 | 2011 |
| Detecção de Alvos na Superfície do Mar em Imagens SAR Orbitais–Área: Rio de Janeiro RL Paes, JA Lorenzzetti, DFM Gherardi Proceedings of the Simpósio de Aplicações Operacionais em Áreas de Defesa, 0 | 2 | |
