Nikola Pavešić

64 papers receiving 889 citations

Peers

Nikola Pavešić
Comparison fields: 5 of 120
  • Computer Vision and Pattern Recognition 578
  • Signal Processing 367
  • Artificial Intelligence 228
  • Information Systems 104
  • Experimental and Cognitive Psychology 77
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S. Palanivel India
Patrick S. P. Wang United States
Krešimir Delač Croatia
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Aggelos Pikrakis Greece
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Citations per field
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Citations per year

Countries citing papers authored by Nikola Pavešić

Since Specialization
Citations

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

Fields of papers citing papers by Nikola Pavešić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nikola Pavešić

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1
Continuous Speech Recognition by a Network of Hidden Markov Models
0
2
Semantic Decomposition of Sentences in the System Supporting Flight Services
0
3
Text-to-speech synthesis : A complete system for the Slovenian language
1
4 7
5
Adaptation of SIFT features for face recognition under varying illumination
20
6 3
7 28
8 19
9 10
10 7
11 2
12 20
13 2
14
Bilingual Speech Recognition for Weather Information Retrieval Dialog System
1
15 0
16 1
17
Hierarchical Model of Multi-Agent System for Spatio-Temproal Rich Domains
1
18 4
19
Recording and labelling of the GOPOLIS slovenian speech database
6
20 1

About Nikola Pavešić

Nikola Pavešić is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 69 papers that have together received 981 indexed citations. Recurring topics across this work include Face and Expression Recognition (19 papers), Biometric Identification and Security (18 papers) and Speech Recognition and Synthesis (15 papers). The work is most often cited by research in Signal Processing (367 citations), Computer Vision and Pattern Recognition (578 citations) and Artificial Intelligence (228 citations). Nikola Pavešić has collaborated with scholars based in Slovenia, Croatia and United Kingdom. Frequent co-authors include Vitomir Štruc, Samo Ribarič, Mohammad-Taghi Vakil-Baghmisheh, Aladdin Ariyaeeinia, France Mihelič, Simon Dobrišek, Jerneja Žganec Gros, Janez Žibert, Denis Trček and Roman Trobec. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, European Journal of Operational Research and Pattern Recognition.

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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