What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- World War II
His main research concerns Photogrammetry, Artificial intelligence, Computer vision, 3D modeling and Point cloud.
Photogrammetry is a subfield of Remote sensing that Fabio Remondino studies.
When carried out as part of a general Artificial intelligence research project, his work on Image is frequently linked to work in Robotics, therefore connecting diverse disciplines of study.
His Image processing, Orientation, Camera resectioning and Feature extraction study, which is part of a larger body of work in Computer vision, is frequently linked to Automation, bridging the gap between disciplines.
Within one scientific family, Fabio Remondino focuses on topics pertaining to Cultural heritage under 3D modeling, and may sometimes address concerns connected to Virtual reality, Multimedia and Visualization.
His studies in Point cloud integrate themes in fields like Noise, Geometric primitive, Commercial software, Statistical classification and Image matching.
His most cited work include:
- UAV for 3D mapping applications: a review (811 citations)
- IMAGE-BASED 3D MODELLING: A REVIEW (620 citations)
- Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning (376 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Photogrammetry, Computer vision, Point cloud and Cultural heritage are his primary areas of study.
His 3D reconstruction, Image, Bundle adjustment, Object and Feature extraction investigations are all subjects of Artificial intelligence research.
His study looks at the intersection of Photogrammetry and topics like 3D modeling with Engineering drawing.
His work on Orientation, Image processing, Camera resectioning and Feature as part of his general Computer vision study is frequently connected to Oblique case, thereby bridging the divide between different branches of science.
His Point cloud research includes elements of Segmentation, Process and Ground truth, Machine learning, Deep learning.
His Cultural heritage study integrates concerns from other disciplines, such as Field, Multimedia, Visualization, Documentation and Data science.
He most often published in these fields:
- Artificial intelligence (39.76%)
- Photogrammetry (40.06%)
- Computer vision (34.12%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (39.76%)
- Photogrammetry (40.06%)
- Point cloud (19.88%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Photogrammetry, Point cloud, Computer vision and 3D reconstruction.
His studies link Machine learning with Artificial intelligence.
His study with Photogrammetry involves better knowledge in Remote sensing.
His studies deal with areas such as Cultural heritage, Lidar, Documentation and 3D city models as well as Point cloud.
Fabio Remondino is interested in Feature, which is a field of Computer vision.
His 3D reconstruction study also includes fields such as
- Pipeline which is related to area like Computer graphics and Data mining,
- Boosting and related Depth map.
Between 2017 and 2021, his most popular works were:
- Graphos – Open - Source Software for photogrammetric applications (28 citations)
- Classification of 3D Digital Heritage (27 citations)
- Photogrammetry of the Human Brain: A Novel Method for Three-Dimensional Quantitative Exploration of the Structural Connectivity in Neurosurgery and Neurosciences. (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- World War II
His scientific interests lie mostly in Artificial intelligence, Point cloud, Photogrammetry, Computer vision and 3D reconstruction.
His research brings together the fields of Cultural heritage and Artificial intelligence.
Fabio Remondino has included themes like Change detection, Remote sensing, Data mining, Cadastre and Ground truth in his Point cloud study.
The various areas that he examines in his Photogrammetry study include Orientation, Lens, Optics and Underwater.
His work on Feature and Depth of field as part of general Computer vision study is frequently linked to Tractography and Human brain, bridging the gap between disciplines.
His studies in 3D reconstruction integrate themes in fields like Pipeline, Open source, Open source software and Engineering drawing.
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