Gabriel Dario Caffaratti

Gabriel Dario Caffaratti
National University of Cuyo | UNCUYO · Intelligent Systems Laboratory, School of Engineering

Information Systems Engineer

About

5
Publications
779
Reads
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3
Citations
Citations since 2016
5 Research Items
3 Citations
20162017201820192020202120220.00.51.01.52.02.53.0
20162017201820192020202120220.00.51.01.52.02.53.0
20162017201820192020202120220.00.51.01.52.02.53.0
20162017201820192020202120220.00.51.01.52.02.53.0
Introduction
I've got a degree in Systems Engineering. University teacher of Artificial Intelligence and development team leader. Ph.D. Candidate in Computer Science. Free software activist. Currently working on Deep Learning Architecture for Forest Detection in Satellite Data.

Publications

Publications (5)
Preprint
Full-text available
Even though a train/test split of the dataset randomly performed is a common practice, could not always be the best approach for estimating performance generalization under some scenarios. The fact is that the usual machine learning methodology can sometimes overestimate the generalization error when a dataset is not representative or when rare and...
Article
Forest detection in remote sensing data is essential for important applications such as detection of area desertification, flooding simulation, forest health analysis, or conversion of digital elevation models. Existing techniques have open issues: they do not generalize well to different scenarios, they lack accuracy, and they require human interv...
Conference Paper
Full-text available
Deep Learning algorithms have achieved great progress in different applications due to their training capabilities, parameter reduction and increased accuracy. Image processing is a particular area that has received recent attention promoted by the growing processing power and data availability. Remote sensing devices provide image-like data that c...
Conference Paper
Full-text available
Processing of data gathered from remote sensing devices like satellite and aircraft-based sensors can provide useful information about important phenomena related to the earth, like volcano shape and activity, glacier and icebergs tracking, urban monitoring, forestation changes, among others. Particularly, forestation detection is useful in differe...
Article
Full-text available
Visual depth recognition through Stereo Matching is an active field of research due to the numerous applications in robotics, autonomous driving, user interfaces, etc. Multiple techniques have been developed in the last two decades to achieve accurate disparity maps in short time. With the arrival of Deep Leaning architectures, different fields of...

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