Yll Haxhimusa

686 citations
14 papers · 142 indexed · h-index 8
Topics
Advanced Image and Video Retrieval Techniques (5 papers)Visual Attention and Saliency Detection (4 papers)Image Retrieval and Classification Techniques (4 papers)

In The Last Decade

Yll Haxhimusa

14 papers receiving 130 citations

Peers

Yll Haxhimusa
Comparison fields: 5 of 57
  • Computer Vision and Pattern Recognition 63
  • Artificial Intelligence 31
  • Signal Processing 24
  • Computational Theory and Mathematics 21
  • Automotive Engineering 20
Replace Wouter Kool with:
Wouter Kool Netherlands
Irene Campari Austria
Haekyu Park United States
Ilija Ilievski Singapore
Terumasa Aoki Japan
Dim P. Papadopoulos United States
Hebah ElGibreen Saudi Arabia
Zhen Qin United States
Pengda Qin China
Zhixing Tan China
Yll Haxhimusa relative to Wouter Kool Netherlands Wouter Kool's profile →
Citations per field
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Countries citing papers authored by Yll Haxhimusa

Since Specialization
Citations

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

Fields of papers citing papers by Yll Haxhimusa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yll Haxhimusa

This figure shows the co-authorship network connecting the top 25 collaborators of Yll Haxhimusa. A scholar is included among the top collaborators of Yll Haxhimusa 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 Yll Haxhimusa. Yll Haxhimusa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
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3 5
4
Classification of gothic and baroque architectural elements
8
5 12
6 2
7 7
8 12
9 10
10 3
11 3
12 46
13 22
14 9

About Yll Haxhimusa

Yll Haxhimusa is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Science Applications, having authored 14 papers that have together received 142 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (5 papers), Visual Attention and Saliency Detection (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (63 citations), Signal Processing (24 citations) and Transportation (13 citations). Yll Haxhimusa has collaborated with scholars based in Austria, United States and Kosovo. Frequent co-authors include Walter G. Kropatsch, Zygmunt Pizlo, Emil Stefanov, Zheng Li, Adrian Ion, Georg Langs, Robert Sablatnig, Edward J. Carpenter, Dávid Földes and Laura Arns. Their work appears in journals such as Pattern Recognition Letters, Image and Vision Computing and Brain stimulation.

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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