Daniel C. Zanotta
Orcid: 0000-0003-2959-6525
According to our database1,
Daniel C. Zanotta
authored at least 29 papers
between 2012 and 2023.
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Bibliography
2023
An assisted multi-frame approach for super-resolution in hyperspectral images of rock samples.
Comput. Geosci., December, 2023
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
Evaluation of Resampling Techniques to Provide Better Synthesized Input Data to Super-Resolution Deep Learning Model Training.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
Clustering Fracture Data in 3D Outcrop Models with Hierarchical Agglomerative Clustering and Fisher Statistics.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
Immersive Paleontological Experience Through Virtual and Augmented Reality Representation.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
2022
Remote. Sens., 2022
Spherical K-Means and Elbow Method Optimizations With Fisher Statistics for 3D Stochastic DFN From Virtual Outcrop Models.
IEEE Access, 2022
Adaptive Segmentation for Discontinuity Detection on Karstified Carbonate Outcrop Images From UAV-SfM Acquisition and Detection Bias Analysis.
IEEE Access, 2022
A Geometric Approach for Hyperspectral and 3D Point Cloud Integration in Natural Scenes.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
Analysis of Machine Learning Techniques for Carbonate Outcrop Image Classification in Landsat 8 Satellite Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
2021
A Multi-Looking Approach for Spatial Super-Resolution on Laboratory-Based Hyperspectral Images.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
Deep Learning Application for Fracture Segmentation Over Outcrop Images from UAV-Based Digital Photogrammetry.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
Kerogen Type Classification in Hydrocarbon Source Rocks Using Hyperspectral Data and Machine Learning.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2020
A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning.
Sensors, 2020
Improving Spatial Resolution of Multispectral Rock Outcrop Images Using RGB Data and Artificial Neural Networks.
Sensors, 2020
A Quantitative Analysis on Different Carbonate Indicators Based on Spaceborne Data in a Controlled Karst Area.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Image Analysis Based On Cognitive Color Attributes For Classification of Environmental Remote Sensing Scenes.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2015
An Adaptive Semisupervised Approach to the Detection of User-Defined Recurrent Changes in Image Time Series.
IEEE Trans. Geosci. Remote. Sens., 2015
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015
2014
Linear Spectral Mixing Model for Identifying Potential Missing Endmembers in Spectral Mixture Analysis.
IEEE Trans. Geosci. Remote. Sens., 2014
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014
Detection of specific changes in image time series by an adaptive change vector analysis.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014
2013
Automatic detection of burned areas in wetlands by remote sensing multitemporal images.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013
2012
Pattern Recognit., 2012
Residual information to estimate uncertainty and improve the spectral linear mixing model solution.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012