Srđan Kitić

696 citations
13 papers · 346 · 1 hit paper · h-index 6

Impact in

Papers in

Srđan Kitić

13 papers receiving 334 citations

Srđan Kitić's Hit Papers

A survey of sound source localization with deep learning methods 2022 · 222 citations
2220+1+2Years since publication50100150200

Peers

Srđan Kitić
Comparison fields: 5 of 42
  • Signal Processing 267
  • Oceanography 68
  • Developmental Biology 8
  • Computational Mechanics 66
  • Computer Vision and Pattern Recognition 51
Replace Despoina Pavlidi with:
Despoina Pavlidi Greece
Alexandre Guérin France
Daniele Salvati Italy
Christine Evers United Kingdom
Qinghua Huang China
Antonio Canclini Italy
Alexander Schmidt Germany
Antoine Deleforge France
Heinrich W. Löllmann Germany
Luiz W. P. Biscainho Brazil
Srđan Kitić relative to Despoina Pavlidi Greece Despoina Pavlidi's profile →
Citations per field
00.5×
Despoina Pavlidi · 1×
Citations per year

Countries citing papers authored by Srđan Kitić

Since Specialization
Citations

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

Fields of papers citing papers by Srđan Kitić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Srđan Kitić, 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 Srđan Kitić Line = papers co-authored together Srđan Kitić links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
A survey of sound source localization with deep learning methods
Hit paper breakdown →
2022222
2 201525
3 202125
4 201521
5 202018
6 202110
7 20225
8 20175
9 20225
10 20174
11
A review of cosparse signal recovery methods applied to sound source localization
20132
12 20232
13 20172

About Srđan Kitić

Srđan Kitić is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics, Oceanography and Mathematical Physics, having authored 13 papers that have together received 346 indexed citations. Recurring topics across this work include Speech and Audio Processing (11 papers), Music and Audio Processing (6 papers), Image and Signal Denoising Methods (4 papers), Underwater Acoustics Research (3 papers), Sparse and Compressive Sensing Techniques (3 papers), Numerical methods in inverse problems (2 papers), Structural Health Monitoring Techniques (1 paper) and Indoor and Outdoor Localization Technologies (1 paper). The work is most often cited by research in Signal Processing (267 citations), Oceanography (68 citations), Developmental Biology (8 citations), Computational Mechanics (66 citations) and Computer Vision and Pattern Recognition (51 citations). Srđan Kitić has collaborated with scholars based in France. Frequent co-authors include Laurent Girin, Alexandre Guérin, Nancy Bertin, Rémi Gribonval, Jérôme Daniel, Laurent Albera, Gilles Puy and Patrick Pérez. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, The Journal of the Acoustical Society of America, IEEE Transactions on Signal Processing, Lecture notes in computer science and Applied and numerical harmonic analysis.

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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