Maja Matetić

503 citations
44 papers · 335 · h-index 11

Impact in

Papers in

Maja Matetić

37 papers receiving 323 citations

Peers

Maja Matetić
Comparison fields: 5 of 84
  • Computer Science Applications 67
  • Food Science 71
  • Analytical Chemistry 25
  • Health Informatics 3
  • Artificial Intelligence 68
Replace Marija Brkić Bakarić with:
Marija Brkić Bakarić Croatia
Rijwan Khan India
Wei Gong China
Slamet Riyadi Indonesia
Samuel Sepúlveda Chile
Domenic T. Sanchez Philippines
Apirat Wanichsombat Thailand
Yaser Hafeez Pakistan
Avneet Kaur India
Oky Dwi Nurhayati Indonesia
Maja Matetić relative to Marija Brkić Bakarić Croatia Marija Brkić Bakarić's profile →
Citations per field
00.5×2.8×
Marija Brkić Bakarić · 1×
Citations per year

Countries citing papers authored by Maja Matetić

Since Specialization
Citations

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

Fields of papers citing papers by Maja Matetić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Maja Matetić, 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 Maja Matetić Line = papers co-authored together Maja Matetić links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201743
2 201733
3 201730
4 202025
5 202419
6 201815
7 202315
8 201514
9 201614
10 202212
11 202111
12 201910
13 20249
14 20219
15 20208
16 20208
17 20227
18 20216
19 20156
20 20185

About Maja Matetić

Maja Matetić is a scholar working on Artificial Intelligence, Computer Science Applications, Information Systems, Plant Science and Computer Networks and Communications, having authored 44 papers that have together received 335 indexed citations. Recurring topics across this work include Online Learning and Analytics (13 papers), Natural Language Processing Techniques (9 papers), Plant Physiology and Cultivation Studies (6 papers), Postharvest Quality and Shelf Life Management (5 papers), Advanced Chemical Sensor Technologies (5 papers), Speech and dialogue systems (4 papers), Food Supply Chain Traceability (4 papers) and Software System Performance and Reliability (4 papers). The work is most often cited by research in Computer Science Applications (67 citations), Food Science (71 citations), Analytical Chemistry (25 citations), Health Informatics (3 citations) and Artificial Intelligence (68 citations). Maja Matetić has collaborated with scholars based in Croatia, China and United Kingdom. Frequent co-authors include Marija Brkić Bakarić, Tomislav Jemrić, Xiaoshuan Zhang, Xiang Wang, Qile He, Zhigang Li, Xinqing Xiao, Huijuan Zhou, Guoxiang Zhang and Marko Vuković. Their work appears in journals such as Applied Sciences, International Journal of Emerging Technologies in Learning (iJET), Electronics, Applied Intelligence and Materials Today Sustainability.

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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