Josip Krapac

610 citations
19 papers · 432 · h-index 8

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Image Retrieval and Classification Techniques
    • Advanced Neural Network Applications
    • Multimodal Machine Learning Applications
    • Video Surveillance and Tracking Methods
    • Remote-Sensing Image Classification

Papers in

Josip Krapac

19 papers receiving 415 citations

Peers

Josip Krapac
Comparison fields: 5 of 56
  • Computer Vision and Pattern Recognition 355
  • Media Technology 78
  • Artificial Intelligence 128
  • Aerospace Engineering 43
  • Signal Processing 10
Replace Md Amirul Islam with:
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Mahyar Najibi United States
Rafi Cohen Israel
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Josip Krapac relative to Md Amirul Islam Canada Md Amirul Islam's profile →
Citations per field
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Citations per year

Countries citing papers authored by Josip Krapac

Since Specialization
Citations

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

Fields of papers citing papers by Josip Krapac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Josip Krapac, 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 Josip Krapac Line = papers co-authored together Josip Krapac links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2011123
2 201098
3 201644
4 200744
5 201734
6 202032
7 201414
8 201912
9 20115
10 20165
11 20185
12 20154
13 20153
14 20152
15 20082
16
[Cycling in Zagreb].
20072
17
Robust Traffic Scene Recognition with a Limited Descriptor Length
20151
18
Spatial Fisher Vectors for Image Categorization
20111
19 20141

About Josip Krapac

Josip Krapac is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Aerospace Engineering and Civil and Structural Engineering, having authored 19 papers that have together received 432 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (14 papers), Domain Adaptation and Few-Shot Learning (7 papers), Image Retrieval and Classification Techniques (6 papers), Advanced Neural Network Applications (6 papers), Video Surveillance and Tracking Methods (3 papers), Robotics and Sensor-Based Localization (3 papers), Infrastructure Maintenance and Monitoring (2 papers) and Vehicle License Plate Recognition (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (355 citations), Media Technology (78 citations), Artificial Intelligence (128 citations), Aerospace Engineering (43 citations) and Signal Processing (10 citations). Josip Krapac has collaborated with scholars based in Croatia, France and Germany. Frequent co-authors include Jakob Verbeek, Frédéric Jurie, Siniša Šegvić, Moray Allan, Tomislav Hrkać, Zoran Kalafatić, Alan Akbik, Roland Vollgraf and Karla Brkić. Their work appears in journals such as Computer Vision and Image Understanding, IEEE Transactions on Intelligent Transportation Systems, Lecture notes in computer science, Computer Vision and Pattern Recognition and PubMed.

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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