Peter Caccetta

71 papers receiving 2.4k citations

Peter Caccetta's Hit Papers

ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data 2020 · 1.4k citations
1.4k0+2+4Years since publication4008001.2k

Peers

Peter Caccetta
Comparison fields: 5 of 141
  • Media Technology 526
  • Environmental Engineering 729
  • Computer Vision and Pattern Recognition 710
  • Ecology 633
  • Global and Planetary Change 407
Replace François Waldner with:
François Waldner Belgium
Olaf Hellwich Germany
Ying Sun China
Raul Queiroz Feitosa Brazil
Silvana Dellepiane Italy
Zhengxin Zhang China
Yun Zhang Canada
Fariba Mohammadimanesh Canada
Dong-Chen He Canada
Peter Caccetta relative to François Waldner Belgium François Waldner's profile →
Citations per field
00.5×1.5×
François Waldner · 1×
Citations per year

Countries citing papers authored by Peter Caccetta

Since Specialization
Citations

This map shows the geographic impact of Peter Caccetta'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 Peter Caccetta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Caccetta more than expected).

Fields of papers citing papers by Peter Caccetta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter Caccetta. 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 Peter Caccetta. The network helps show where Peter Caccetta may publish in the future.

Co-authors

The 25 scholars most cited alongside Peter Caccetta, 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 Peter Caccetta Line = papers co-authored together Peter Caccetta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data
Hit paper breakdown →
20201358
2 201495
3 201294
4 202075
5 200260
6 201152
7 202046
8 201046
9 201342
10 201037
11 202236
12 200435
13 202034
14 201431
15 202130
16 201129
17 201027
18 202127
19 200027
20
The Land Monitor Project
200024

About Peter Caccetta

Peter Caccetta is a scholar working on Environmental Engineering, Ecology, Artificial Intelligence, Global and Planetary Change and Aerospace Engineering, having authored 74 papers that have together received 2.5k indexed citations. Recurring topics across this work include Remote Sensing and LiDAR Applications (32 papers), Soil Geostatistics and Mapping (30 papers), Remote Sensing in Agriculture (29 papers), Geochemistry and Geologic Mapping (10 papers), Land Use and Ecosystem Services (8 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (8 papers), Urban Heat Island Mitigation (8 papers) and Remote-Sensing Image Classification (6 papers). The work is most often cited by research in Media Technology (526 citations), Environmental Engineering (729 citations), Computer Vision and Pattern Recognition (710 citations), Ecology (633 citations) and Global and Planetary Change (407 citations). Peter Caccetta has collaborated with scholars based in Australia, China and Greece. Frequent co-authors include Chen Wu, François Waldner, Foivos I. Diakogiannis, J. Wallace, Eric Lehmann, Suzanne Furby, Xiaoliang Wu, Riccardo Paolini, M. Santamouris and Hassan Saeed Khan. Their work appears in journals such as International Journal of Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Journal of Environmental Quality and International Journal of Image and Data Fusion.

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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