• Home >
  • Profile-Laura Lopez Fuentes

Dr. Laura Lopez Fuentes

  • Department:    CVI²
  • Postal Address: CVI², Campus Kirchberg, Université du Luxembourg 6, rue Richard Coudenhove-KalergiL-1359 Luxembourg



Dr. Lopez holds a M.Sc in Computer Vision from the Autonomous university of Barcelona.  She received her Ph.D. in computer vision from the University of the Balearic Islands (Spain) in 2021. She carried out her Ph.D. in collaboration with the Computer Vision Center in Barcelona and the private company AnsuR Technologies based in Oslo (Norway). Her research has been applied in a wide range of fields, from predicting and detecting natural disasters to spotting forgery in images and data. In 2021, Dr. Lopez joined the University of Luxembourg in the Computer Vision, Imaging, and Machine Intelligence Research Group to continue working on computer vision and data science applied to cybersecurity. Additionally, she holds a M.Sc in Teaching specialized in Mathematics.  

Research Interests

  • Computer Vision
  • Deep Learning
  • Anomaly Detection
  • Emergency Management



Zolfaghari Bengar, Javad, Joost van de Weijer, Laura Lopez Fuentes, and Bogdan Raducanu. 2021. “Class-Balanced Active Learning for Image Classification.” arXiv e-Prints, arXiv–2110.

Wang, Yaxing, Héctor Laria, Joost van de Weijer, Laura Lopez-Fuentes, and Bogdan Raducanu. 2021. “TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets.” In Proceedings of the IEEE/CVF International Conference on Computer Vision, 14010–19.


Lopez-Fuentes, Laura, Alessandro Farasin, Mirko Zaffaroni, Harald Skinnemoen, and Paolo Garza. 2020. “Deep Learning Models for Road Passability Detection During Flood Events Using Social Media Data.” Applied Sciences 10 (24): 8783.


Zaffaroni, Mirko, Laura Lopez-Fuentes, Alessandro Farasin, Paolo Garza, Harald Skinnemoen, et al. 2019. “AI-Based Flood Event Understanding and Quantification Using Online Media and Satellite Data.”


Lopez-Fuentes, Laura, Alessandro Farasin, Harald Skinnemoen, and Paolo Garza. 2018. “Deep Learning Models for Passability Detection of Flooded Roads.” In MediaEval.

Lopez-Fuentes, Laura, Joost van de Weijer, Manuel González-Hidalgo, Harald Skinnemoen, and Andrew D Bagdanov. 2018. “Review on Computer Vision Techniques in Emergency Situations.” Multimedia Tools and Applications 77 (13): 17069–107.


Lopez-Fuentes, Laura, Andrew D Bagdanov, Joost Van De Weijer, and Harald Skinnemoen. 2017. “Bandwidth Limited Object
Recognition in High Resolution Imagery
.” In 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), 1197–1205. IEEE.

Lopez-Fuentes, Laura, Sebastia Massanet, and Manuel González-Hidalgo. 2017. “Image Vignetting Reduction via a Maximization of Fuzzy Entropy.” In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1–6. IEEE.

Lopez-Fuentes, Laura, Claudio Rossi, and Harald Skinnemoen. 2017. “River Segmentation for Flood Monitoring.” In 2017 IEEE International Conference on Big Data (Big Data), 3746–49. IEEE.

Lopez-Fuentes, Laura, Joost van de Weijer, Marc Bolanos, and Harald Skinnemoen. 2017. “Multi-Modal Deep Learning Approach for Flood Detection.” MediaEval 17: 13–15.


Lopez-Fuentes, Laura, Gabriel Oliver, and Sebastia Massanet. 2015. “Revisiting Image Vignetting Correction by Constrained Minimization of Log-Intensity Entropy.” In International Work-Conference on Artificial Neural Networks, 450–63. Springer, Cham.