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ORCIDLaura Elena Cue La Rosa
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2020 – today
- 2024
[j5]Omid Ghorbanzadeh
, Hejar Shahabi, Sepideh Tavakkoli Piralilou, Alessandro Crivellari, Laura Elena Cue La Rosa, Clement Atzberger, Jonathan Li, Pedram Ghamisi:
Contrastive Self-Supervised Learning for Globally Distributed Landslide Detection. IEEE Access 12: 118453-118466 (2024)- 2023
- [j4]Laura Elena Cué La Rosa, Dário Augusto Borges Oliveira, Pedram Ghamisi:
Learning Crop-Type Mapping From Regional Label Proportions in Large-Scale SAR and Optical Imagery. IEEE Trans. Geosci. Remote. Sens. 61: 1-15 (2023) - 2022
- [j3]Laura Elena Cué La Rosa, Dário A. B. Oliveira, Maciel Zortea, Bruno Holtz Gemignani, Raul Queiroz Feitosa:
Learning Geometric Features for Improving the Automatic Detection of Citrus Plantation Rows in UAV Images. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [c8]Laura Elena Cué La Rosa, Dário Augusto Borges Oliveira:
Learning from Label Proportions with Prototypical Contrastive Clustering. AAAI 2022: 2153-2161 - [c7]Paolo Fraccaro, Nikola Stoyanov, Zaheed Gaffoor, Laura Elena Cue La Rosa, Jitendra Singh, Tatsuya Ishikawa, Blair Edwards, Anne Jones, Komminist Weldemariam:
Deploying an Artificial Intelligence Application to Detect Flood from Sentinel 1 Data. AAAI 2022: 12489-12495 - [c6]Laura Elena Cué La Rosa, Dário Augusto Borges Oliveira, Samuel T. Thiele, Pedram Ghamisi, Richard Gloaguen:
Weak-Supervision Based on Label Proportions for Earth Observation Applications from Optical and Hyperspectral Imagery. CDCEO@IJCAI 2022: 79-85 - [i2]Laura Elena Cue La Rosa, Dário A. B. Oliveira, Pedram Ghamisi:
Learning crop type mapping from regional label proportions in large-scale SAR and optical imagery. CoRR abs/2208.11607 (2022) - 2021
- [c5]Laura Elena Cue La Rosa, Dário Augusto Borges Oliveira, Raul Queiroz Feitosa:
End-to-End CNN-CRFs for Multi-date Crop Classification Using Multitemporal Remote Sensing Image Sequences. CIKM Workshops 2021 - [c4]Laura Elena Cué La Rosa, Dário A. B. Oliveira, Raul Queiroz Feitosa:
Investigating Fusion Strategies on Encoder-Decoder Networks for Crop Segmentation Using SAR and Optical Image Sequences. IGARSS 2021: 2405-2408 - [c3]Daliana Lobo Torres, Laura Elena Cué La Rosa, Dário A. B. Oliveira, Raul Queiroz Feitosa:
Evaluation of Unsupervised Deep Clustering Methods for Crop Classification Using SAR Image Sequences. IGARSS 2021: 4240-4243 - [i1]Laura Elena Cué La Rosa, Camile Sothe, Raul Queiroz Feitosa, Cláudia Maria de Almeida, Marcos Benedito Schimalski, Dário Augusto Borges Oliveira:
Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data. CoRR abs/2106.00799 (2021) - 2020
- [j2]Daliana Lobo Torres, Raul Queiroz Feitosa, Patrick Nigri Happ, Laura Elena Cue La Rosa, José Marcato Junior, José Augusto Correa Martins, Patrik Olã Bressan, Wesley Nunes Gonçalves, Veraldo Liesenberg:
Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery. Sensors 20(2): 563 (2020)
2010 – 2019
- 2019
- [j1]Laura Elena Cue La Rosa, Raul Queiroz Feitosa, Patrick Nigri Happ, Ieda Del'Arco Sanches, Gilson Alexandre Ostwald Pedro da Costa:
Combining Deep Learning and Prior Knowledge for Crop Mapping in Tropical Regions from Multitemporal SAR Image Sequences. Remote. Sens. 11(17): 2029 (2019) - 2018
- [c2]Laura Elena Cue La Rosa, Patrick Nigri Happ, Raul Queiroz Feitosa:
Dense Fully Convolutional Networks for Crop Recognition from Multitemporal SAR Image Sequences. IGARSS 2018: 7460-7463 - 2017
- [c1]Jose David Bermudez Castro, Raul Queiroz Feitosa, Laura Elena Cue La Rosa, Pedro Marco Achanccaray Diaz, Ieda Del'Arco Sanches:
A Comparative Analysis of Deep Learning Techniques for Sub-Tropical Crop Types Recognition from Multitemporal Optical/SAR Image Sequences. SIBGRAPI 2017: 382-389
Coauthor Index
aka: Dário Augusto Borges Oliveira
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