A Comparative Analysis of Deep Learning Techniques for Sub-Tropical Crop Types Recognition from Multitemporal Optical/SAR Image Sequences. - Jose David Bermudez Castro; Raul Queiroz Feitosa; Laura Elena Cue La Rosa; Pedro Marco Achanccaray Diaz; Ieda Del'Arco Sanches (SIBGRAPI, 2017)

Dense Fully Convolutional Networks for Crop Recognition from Multitemporal SAR Image Sequences. - Laura Elena Cue La Rosa; Patrick Nigri Happ; Raul Queiroz Feitosa (IGARSS, 2018)

Combining Deep Learning and Prior Knowledge for Crop Mapping in Tropical Regions from Multitemporal SAR Image Sequences. - Laura Elena Cue La Rosa; Raul Queiroz Feitosa; Patrick Nigri Happ; Ieda Del'Arco Sanches; Gilson Alexandre Ostwald Pedro da Costa (Remote. Sens., 2019)

Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery. - 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 (Sensors, 2020)

End-to-End CNN-CRFs for Multi-date Crop Classification Using Multitemporal Remote Sensing Image Sequences. - Laura Elena Cue La Rosa; Dário Augusto Borges Oliveira; Raul Queiroz Feitosa (CIKM Workshops, 2021)

Investigating Fusion Strategies on Encoder-Decoder Networks for Crop Segmentation Using SAR and Optical Image Sequences. - Laura Elena Cué La Rosa; Dário A. B. Oliveira; Raul Queiroz Feitosa (IGARSS, 2021)

Evaluation of Unsupervised Deep Clustering Methods for Crop Classification Using SAR Image Sequences. - Daliana Lobo Torres; Laura Elena Cué La Rosa; Dário A. B. Oliveira; Raul Queiroz Feitosa (IGARSS, 2021)

Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data. - Laura Elena Cué La Rosa; Camile Sothe; Raul Queiroz Feitosa; Cláudia Maria de Almeida; Marcos Benedito Schimalski; Dário Augusto Borges Oliveira (CoRR, 2021)

Deploying an Artificial Intelligence Application to Detect Flood from Sentinel 1 Data. - Paolo Fraccaro; Nikola Stoyanov; Zaheed Gaffoor; Laura Elena Cue La Rosa; Jitendra Singh; Tatsuya Ishikawa; Blair Edwards; Anne Jones; Komminist Weldemariam (AAAI, 2022)

Learning from Label Proportions with Prototypical Contrastive Clustering. - Laura Elena Cué La Rosa; Dário Augusto Borges Oliveira (AAAI, 2022)

Weak-Supervision Based on Label Proportions for Earth Observation Applications from Optical and Hyperspectral Imagery. - Laura Elena Cué La Rosa; Dário Augusto Borges Oliveira; Samuel T. Thiele; Pedram Ghamisi; Richard Gloaguen (CDCEO@IJCAI, 2022)

Learning Geometric Features for Improving the Automatic Detection of Citrus Plantation Rows in UAV Images. - Laura Elena Cué La Rosa; Dário A. B. Oliveira; Maciel Zortea; Bruno Holtz Gemignani; Raul Queiroz Feitosa (IEEE Geosci. Remote. Sens. Lett., 2022)

Learning Crop-Type Mapping From Regional Label Proportions in Large-Scale SAR and Optical Imagery. - Laura Elena Cué La Rosa; Dário Augusto Borges Oliveira; Pedram Ghamisi (IEEE Trans. Geosci. Remote. Sens., 2023)

Contrastive Self-Supervised Learning for Globally Distributed Landslide Detection. - Omid Ghorbanzadeh; Hejar Shahabi; Sepideh Tavakkoli Piralilou; Alessandro Crivellari; Laura Elena Cue La Rosa; Clement Atzberger; Jonathan Li 001; Pedram Ghamisi (IEEE Access, 2024)

Harnessing deep learning and CRF for prior-knowledge modeling of crop dynamics. - Laura Elena Cué La Rosa; Dário Augusto Borges Oliveira; Raul Queiroz Feitosa (Int. J. Appl. Earth Obs. Geoinformation, 2025)