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Fingerprint Dive into the research topics where Diego Marcos Gonzalez is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 4 Similar Researchers
Neural networks Engineering & Materials Science
Animals Engineering & Materials Science
Unmanned aerial vehicles (UAV) Engineering & Materials Science
Curricula Engineering & Materials Science
Antennas Engineering & Materials Science
train Earth & Environmental Sciences
Mammals Engineering & Materials Science
field method Earth & Environmental Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2018 2019

  • 5 Conference contribution
  • 4 Paper
  • 2 Article
  • 1 internal PhD, WU

Best practices to train deep models on imbalanced datasets—a case study on animal detection in aerial imagery

Kellenberger, B., Marcos, D. & Tuia, D., 1 Jan 2019, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Proceedings. Brefeld, U., Marascu, A., Pinelli, F., Curry, E., MacNamee, B., Hurley, N., Daly, E. & Berlingerio, M. (eds.). Springer Verlag, p. 630-634 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11053 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Best Practice
Curricula
Recommendations
Animals
Antennas

Injecting spatial priors in Earth observation with machine vision

Gonzalez, D., 2019, Wageningen: Wageningen University. 130 p.

Research output: Thesisinternal PhD, WUAcademic

Open Access
Open Access
Curricula
Animals
Antennas
Neural networks
2 Citations (Scopus)

Correcting Misaligned Rural Building Annotations in Open Street Map Using Convolutional Neural Networks Evidence

Vargas-Munoz, J. E., Marcos, D., Lobry, S., dos Santos, J. A., Falcao, A. X. & Tuia, D., 5 Nov 2018, 2018 IEEE International Geoscience & Remote Sensing Symposium Proceedings: Observing, Understanding And Forecasting The Dynamics Of Our Planet. IEEE Xplore, p. 1284-1287

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

field method
train
imagery
developing world
alignment

Deep learning based methods for building segmentation from remote sensing data

Lobry, S., Marcos Gonzalez, D., Vargas Munoz, J., Kellenberger, B. A., Srivastava, S. & Tuia, D., 2018. 4 p.

Research output: Contribution to conferencePaperAcademic

Projects 2017 2019