Thomas A. Ciarfuglia

831 citations
29 papers · 544 indexed · h-index 11

Thomas A. Ciarfuglia

26 papers receiving 524 citations

Peers

Thomas A. Ciarfuglia
Comparison fields: 5 of 58
  • Computer Vision and Pattern Recognition 406
  • Aerospace Engineering 300
  • Media Technology 73
  • Geology 32
  • Environmental Engineering 29
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Citations per year

Countries citing papers authored by Thomas A. Ciarfuglia

Since Specialization
Citations

This map shows the geographic impact of Thomas A. Ciarfuglia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Thomas A. Ciarfuglia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas A. Ciarfuglia more than expected).

Fields of papers citing papers by Thomas A. Ciarfuglia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas A. Ciarfuglia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Thomas A. Ciarfuglia. The network helps show where Thomas A. Ciarfuglia may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Thomas A. Ciarfuglia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas A. Ciarfuglia Line = papers co-authored together Thomas A. Ciarfuglia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20250
4 202410
5 20242
6 20242
7 202327
8 201941
9
Towards Monocular Digital Elevation Model (DEM) Estimation by Convolutional Neural Networks - Application on Synthetic Aperture Radar Images
20182
10 201842
11 201737
12 201747
13 201665
14 20166
15 20161
16
A prototype of radar-drone system for measuring the surface flow velocity at river sites and discharge estimation
20151
17 2015138
18 20141
19 201317
20 201210

About Thomas A. Ciarfuglia

Thomas A. Ciarfuglia is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Environmental Engineering, having authored 29 papers that have together received 544 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (13 papers), Advanced Image and Video Retrieval Techniques (10 papers), Smart Agriculture and AI (7 papers), Indoor and Outdoor Localization Technologies (5 papers), Advanced Vision and Imaging (5 papers), Food Supply Chain Traceability (3 papers), Remote Sensing and LiDAR Applications (3 papers) and Robotic Path Planning Algorithms (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (406 citations), Aerospace Engineering (300 citations) and Media Technology (73 citations). Thomas A. Ciarfuglia has collaborated with scholars based in Italy, Netherlands and Switzerland. Frequent co-authors include Gabriele Costante, Paolo Valigi, Michele Mancini, Elisa Ricci, Silvia Cascianelli, Mario Luca Fravolini, Daniele Nardi, Jeffrey Delmerico, Davide Scaramuzza and Mulham Fawakherji. Their work appears in journals such as IEEE Robotics and Automation Letters, Robotics and Autonomous Systems, Computers and Electronics in Agriculture, IEEE Transactions on Multimedia and International Journal of Modelling Identification and Control.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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