Giorgio Morales

Orcid: 0000-0003-2911-8558

According to our database1, Giorgio Morales authored at least 13 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Univariate Skeleton Prediction in Multivariate Systems Using Transformers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024

Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
Improved Yield Prediction of Winter Wheat Using a Novel Two-Dimensional Deep Regression Neural Network Trained via Remote Sensing.
Sensors, 2023

Counterfactual Explanations of Neural Network-Generated Response Curves.
Proceedings of the International Joint Conference on Neural Networks, 2023

2022
Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation.
CoRR, 2022

2021
Hyperspectral Dimensionality Reduction Based on Inter-Band Redundancy Analysis and Greedy Spectral Selection.
Remote. Sens., 2021

Two-dimensional Deep Regression for Early Yield Prediction of Winter Wheat.
CoRR, 2021

Hyperspectral Band Selection for Multispectral Image Classification with Convolutional Networks.
Proceedings of the International Joint Conference on Neural Networks, 2021

2019
Estimation of 2D Velocity Model using Acoustic Signals and Convolutional Neural Networks.
CoRR, 2019

End-to-end Cloud Segmentation in High-Resolution Multispectral Satellite Imagery Using Deep Learning.
CoRR, 2019

Detecting Violent Robberies in CCTV Videos Using Deep Learning.
Proceedings of the Artificial Intelligence Applications and Innovations, 2019

2018
Shadow Removal in High-Resolution Satellite Images Using Conditional Generative Adversarial Networks.
Proceedings of the Information Management and Big Data, 5th International Conference, 2018

Cloud Detection in High-Resolution Multispectral Satellite Imagery Using Deep Learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018


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