Pau Panareda Busto

732 citations
5 papers · 444 indexed · 1 hit paper · h-index 4
Topics
Multimodal Machine Learning Applications (2 papers)Advanced Vision and Imaging (2 papers)Domain Adaptation and Few-Shot Learning (2 papers)
Partner nations
GermanySpain

In The Last Decade

Pau Panareda Busto

5 papers receiving 436 citations

Hit Papers

Open Set Domain Adaptation20172026202020232017100200300

Peers

Pau Panareda Busto
Comparison fields: 5 of 56
  • Artificial Intelligence 334
  • Computer Vision and Pattern Recognition 290
  • Cancer Research 43
  • Radiology, Nuclear Medicine and Imaging 38
  • Control and Systems Engineering 31
Replace Qianfen Jiao with:
Qianfen Jiao China
Shuhao Cui China
Fabio Maria Carlucci Italy
Yukang Ding China
Fei Pan China
Zhihe Lu China
Dapeng Hu China
Guanhang Wu United States
Christian Simon Australia
Pau Panareda Busto relative to Qianfen Jiao China Qianfen Jiao's profile →
Citations per field
00.5×10×15×18.3×
Qianfen Jiao · 1×
Citations per year

Countries citing papers authored by Pau Panareda Busto

Since Specialization
Citations

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

Fields of papers citing papers by Pau Panareda Busto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pau Panareda Busto. 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 Pau Panareda Busto. The network helps show where Pau Panareda Busto may publish in the future.

Co-authorship network of co-authors of Pau Panareda Busto

This figure shows the co-authorship network connecting the top 25 collaborators of Pau Panareda Busto. A scholar is included among the top collaborators of Pau Panareda Busto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pau Panareda Busto. Pau Panareda Busto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
#WorkIndexed citations
1 65
2 2
3
Open Set Domain Adaptationbreakdown →
355
4 12
5 10

About Pau Panareda Busto

Pau Panareda Busto is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Ocean Engineering, having authored 5 papers that have together received 444 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Advanced Vision and Imaging (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (290 citations), Artificial Intelligence (334 citations) and Cancer Research (43 citations). Pau Panareda Busto has collaborated with scholars based in Germany and Spain. Frequent co-authors include Jüergen Gall, Ahsan Iqbal, Joerg Liebelt, Marc Stamminger and Sylvain Lefèbvre. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Vision and Image Understanding and Eurographics.

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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