John E. Vargas-Munoz

Orcid: 0000-0001-7483-8963

According to our database1, John E. Vargas-Munoz authored at least 14 papers between 2016 and 2024.

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Bibliography

2024
Estimating Fine-Grained Population Growth Rates from Coarse Census Data.
Proceedings of the IGARSS 2024, 2024

2022
Fine-grained Population Mapping from Coarse Census Counts and Open Geodata.
CoRR, 2022

Towards Efficient Correction of Coconut Tree Detection Errors.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021
Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient.
Int. J. Geogr. Inf. Sci., 2021

Mapping Vulnerable Populations with AI.
CoRR, 2021

2020
Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data.
Int. J. Geogr. Inf. Sci., 2020

2019
An Iterative Spanning Forest Framework for Superpixel Segmentation.
IEEE Trans. Image Process., 2019

Understanding urban landuse from the above and ground perspectives: a deep learning, multimodal solution.
CoRR, 2019

Correcting rural building annotations in OpenStreetMap using convolutional neural networks.
CoRR, 2019

Interactive Coconut Tree Annotation Using Feature Space Projections.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Correcting Misaligned Rural Building Annotations in Open Street Map Using Convolutional Neural Networks Evidence.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Multilabel Building Functions Classification from Ground Pictures using Convolutional Neural Networks.
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, 2018

2017
Post classification smoothing in sub-decimeter resolution images with semi-supervised label propagation.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

2016
Behavior Knowledge Space-Based Fusion for Copy-Move Forgery Detection.
IEEE Trans. Image Process., 2016


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