Emrullah Acar

32 papers receiving 281 citations

Peers

Emrullah Acar
Comparison fields: 5 of 84
  • Environmental Engineering 69
  • Computer Vision and Pattern Recognition 52
  • Virology 11
  • Media Technology 22
  • Analytical Chemistry 22
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José Maurício Portugal
R Swetha India
G. M. Atiqur Rahaman Bangladesh
Fei Tong China
Mohammad Alkhaleefah Taiwan
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Panle Li China
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Countries citing papers authored by Emrullah Acar

Since Specialization
Citations

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

Fields of papers citing papers by Emrullah Acar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Emrullah Acar, 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 Emrullah Acar Line = papers co-authored together Emrullah Acar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201732
2 201930
3 202026
4 202022
5
The Texture Feature Extraction of Agricultural Field Images by HOG Algorithms and Soil Moisture Estimation based on the Texture Features
201621
6 201918
7 202216
8 202114
9 202313
10
EXTRACTION OF TEXTURE FEATURES FROM LOCAL IRIS AREAS BY GLCM AND IRIS RECOGNITION SYSTEM BASED ON KNN
201611
11 202310
12 20228
13 20228
14 20227
15 20207
16 20206
17 20236
18 20226
19 20156
20 20215

About Emrullah Acar

Emrullah Acar is a scholar working on Environmental Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Plant Science and Radiology, Nuclear Medicine and Imaging, having authored 36 papers that have together received 295 indexed citations. Recurring topics across this work include Smart Agriculture and AI (6 papers), Soil Moisture and Remote Sensing (5 papers), Spectroscopy and Chemometric Analyses (4 papers), Remote-Sensing Image Classification (4 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (4 papers), AI in cancer detection (4 papers), Remote Sensing and Land Use (3 papers) and Remote Sensing in Agriculture (3 papers). The work is most often cited by research in Environmental Engineering (69 citations), Computer Vision and Pattern Recognition (52 citations), Virology (11 citations), Media Technology (22 citations) and Analytical Chemistry (22 citations). Emrullah Acar has collaborated with scholars based in Türkiye and United States. Frequent co-authors include Mehmet Siraç Özerdem, Ömer Faruk Ertuğrul, Ömer Türk, Burak Berk Üstündağ, Musa Yılmaz, Tahir Çetin Akıncı, Burhan Ergen, Abdullah Kaya, Veysi Akpolat and Emrah Irmak. Their work appears in journals such as Computers and Electronics in Agriculture, IEEE Access, Multimedia Tools and Applications, Zeitschrift für Medizinische Physik and PLoS ONE.

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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