Josip Krapac

608 total citations
13 papers, 288 citations indexed

About

Josip Krapac is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Josip Krapac has authored 13 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Media Technology. Recurrent topics in Josip Krapac's work include Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Josip Krapac is often cited by papers focused on Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Josip Krapac collaborates with scholars based in Croatia, France and Spain. Josip Krapac's co-authors include Jakob Verbeek, Frédéric Jurie, Siniša Šegvić, Moray Allan, Alan Akbik, Roland Vollgraf and Karla Brkić and has published in prestigious journals such as IEEE Transactions on Intelligent Transportation Systems, Computer Vision and Image Understanding and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Josip Krapac

13 papers receiving 282 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Josip Krapac Croatia	6	232	93	54	12	9	13	288
Wenchi Ma United States	7	144 0.6×	81 0.9×	26 0.5×	11 0.9×	7 0.8×	9	202
Lintao Zheng China	9	221 1.0×	43 0.5×	60 1.1×	12 1.0×	7 0.8×	34	278
Haoran Wang China	5	169 0.7×	169 1.8×	31 0.6×	12 1.0×	7 0.8×	12	274
Akio Shio Japan	7	272 1.2×	32 0.3×	63 1.2×	17 1.4×	9 1.0×	17	303
Hui Yin China	9	190 0.8×	38 0.4×	66 1.2×	10 0.8×	7 0.8×	33	277
Fabio Cermelli Italy	8	222 1.0×	237 2.5×	21 0.4×	14 1.2×	13 1.4×	13	323
Sungrae Park South Korea	2	265 1.1×	92 1.0×	77 1.4×	4 0.3×	2 0.2×	3	306
Geewook Kim Japan	4	262 1.1×	103 1.1×	78 1.4×	4 0.3×	2 0.2×	10	318

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-authorship network of co-authors of Josip Krapac

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

All Works

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13 of 13 papers shown

Akbik, Alan, et al.. (2020). Task-Aware Representation of Sentences for Generic Text Classification. 3202–3213. 26 indexed citations

Brkić, Karla, et al.. (2019). Traffic Scene Classification on a Representation Budget. IEEE Transactions on Intelligent Transportation Systems. 21(1). 336–345. 12 indexed citations

Krapac, Josip, et al.. (2018). Sparse weakly supervised models for object localization in road environment. Computer Vision and Image Understanding. 176-177. 9–21. 5 indexed citations

Krapac, Josip & Siniša Šegvić. (2017). Ladder-Style DenseNets for Semantic Segmentation of Large Natural Images. 238–245. 33 indexed citations

Brkić, Karla, et al.. (2015). Robust Traffic Scene Recognition with a Limited Descriptor Length. Computer Vision and Pattern Recognition. 1. 1 indexed citations

Krapac, Josip & Siniša Šegvić. (2015). Weakly Supervised Object Localization with Large Fisher Vectors. 44–53. 2 indexed citations

Krapac, Josip, et al.. (2014). Convolutional Neural Networks for Croatian Traffic Signs Recognition. 15–20. 1 indexed citations

Brkić, Karla, et al.. (2014). Image representations on a budget: Traffic scene classification in a restricted bandwidth scenario. 2. 845–852. 13 indexed citations

Krapac, Josip, Jakob Verbeek, & Frédéric Jurie. (2011). Spatial Fisher Vectors for Image Categorization. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations

10.

Krapac, Josip, Jakob Verbeek, & Frédéric Jurie. (2011). Learning Tree-structured Quantizers for Image Categorization. HAL (Le Centre pour la Communication Scientifique Directe). 47.1–47.11. 4 indexed citations

11.

Krapac, Josip, Jakob Verbeek, & Frédéric Jurie. (2011). Modeling spatial layout with fisher vectors for image categorization. HAL (Le Centre pour la Communication Scientifique Directe). 1487–1494. 102 indexed citations

12.

Krapac, Josip, et al.. (2010). Improving web image search results using query-relative classifiers. HAL (Le Centre pour la Communication Scientifique Directe). 1094–1101. 86 indexed citations

13.

Krapac, Josip, et al.. (2007). [Cycling in Zagreb].. PubMed. 61 Suppl 1. 27–31. 2 indexed citations

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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