D. Brzaković

1.1k citations
50 papers · 804 · h-index 13

Impact in

Papers in

D. Brzaković

43 papers receiving 739 citations

Peers

D. Brzaković
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 407
  • Radiology, Nuclear Medicine and Imaging 294
  • Artificial Intelligence 382
  • Industrial and Manufacturing Engineering 100
  • Media Technology 87
Replace Michael D. Heath with:
Michael D. Heath United States
Hidefumi Kobatake Japan
Yongzhao Du China
S.B. Gokturk United States
Bertrand Granado France
R. P. Kruger United States
Bisser Raytchev Japan
Jintai Chen China
G. Valli Italy
Volodymyr Ponomaryov Mexico
D. Brzaković relative to Michael D. Heath United States Michael D. Heath's profile →
Citations per field
00.5×1.6×
Michael D. Heath · 1×
Citations per year

Countries citing papers authored by D. Brzaković

Since Specialization
Citations

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

Fields of papers citing papers by D. Brzaković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside D. Brzaković, 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 D. Brzaković Line = papers co-authored together D. Brzaković links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1990189
2 2002115
3 200268
4 199753
5 200347
6 199640
7 199337
8 198937
9 199726
10 199121
11 199818
12 199015
13 199314
14 200212
15 199410
16 200210
17 19978
18 19918
19 19967
20 19956

About D. Brzaković

D. Brzaković is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Industrial and Manufacturing Engineering and Radiology, Nuclear Medicine and Imaging, having authored 50 papers that have together received 804 indexed citations. Recurring topics across this work include AI in cancer detection (13 papers), Industrial Vision Systems and Defect Detection (9 papers), Medical Image Segmentation Techniques (9 papers), Image and Signal Denoising Methods (9 papers), Advanced Image Fusion Techniques (7 papers), Image and Object Detection Techniques (7 papers), Digital Radiography and Breast Imaging (6 papers) and Image Retrieval and Classification Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (407 citations), Radiology, Nuclear Medicine and Imaging (294 citations), Artificial Intelligence (382 citations), Industrial and Manufacturing Engineering (100 citations) and Media Technology (87 citations). D. Brzaković has collaborated with scholars based in United States, Serbia and Australia. Frequent co-authors include Predrag R. Bakić, Xiaobo Luo, Michael Albert, Andrew D. A. Maidment, Hamed Sari‐Sarraf, Rafael C. González, A. Liakopoulos, Christos Georgakis, Matthew J. Watson and Ziwei Zhu. Their work appears in journals such as Medical Physics, Pattern Recognition, IEEE Transactions on Signal Processing, IEEE Transactions on Robotics and Automation and Image and Vision Computing.

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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