Dejan Gjorgjevikj

1.3k citations
19 papers · 847 indexed · 1 hit paper · h-index 10

Dejan Gjorgjevikj

18 papers receiving 806 citations

Hit Papers

An extensive experimental comparison of methods for multi...4972012202620162021100200300400

Peers

Dejan Gjorgjevikj
Comparison fields: 5 of 110
  • Artificial Intelligence 538
  • Computer Vision and Pattern Recognition 264
  • Information Systems 184
  • Signal Processing 61
  • Computer Science Applications 21
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Countries citing papers authored by Dejan Gjorgjevikj

Since Specialization
Citations

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

Fields of papers citing papers by Dejan Gjorgjevikj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 15 scholars most cited alongside Dejan Gjorgjevikj, 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 Dejan Gjorgjevikj Line = papers co-authored together Dejan Gjorgjevikj links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 202122
2 20219
3
Precision Apiculture – IoT System for remote monitoring of honeybee colonies
20202
4
Data Collection Module for Human Activity Recognition
20181
5 201715
6 20169
7 201525
8 201438
9 20147
10 20133
11
An extensive experimental comparison of methods for multi-label learningbreakdown →
2012497
12
Hierarchical classification architectures applied to Magnetic Resonance Images
20112
13 201126
14 20113
15
Classification of magnetic resonance images
20103
16
Towards Improving Magnetic Resonance Image Classification
20101
17
Ensembles of Binary SVM Decision Trees
20103
18
A Multi-class SVM Classifier Utilizing Binary Decision Tree
2009143
19 200938

About Dejan Gjorgjevikj

Dejan Gjorgjevikj is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Software, having authored 19 papers that have together received 847 indexed citations. Recurring topics across this work include Face and Expression Recognition (6 papers), Image Retrieval and Classification Techniques (6 papers), Text and Document Classification Technologies (6 papers), Machine Learning in Bioinformatics (5 papers), Neural Networks and Applications (4 papers), Spam and Phishing Detection (2 papers), Machine Fault Diagnosis Techniques (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (538 citations), Computer Vision and Pattern Recognition (264 citations) and Information Systems (184 citations). Dejan Gjorgjevikj has collaborated with scholars based in North Macedonia, Slovenia and China. Frequent co-authors include Gjorgji Madjarov, Sašo Džeroski, Dragi Kocev, Ivan Chorbev, Eftim Zdravevski, Andrea Kulakov, Petre Lameski, Shaohui Zhang, Chuan Li and Jianyu Long. Their work appears in journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Measurement Science and Technology.

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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