World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
6234
World Ranking
12027
National Ranking
22

Salih Güneş publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Salih Güneş sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 84 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Salih Güneş D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Salih Güneş sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Salih Güneş is affiliated with Konya Technical University in Turkey. Their research primarily focuses on engineering and computer science, with notable contributions across several subfields. These include electrical and electronic engineering, computer networks and communications, computer vision and pattern recognition, neurology, and cognitive neuroscience.

The main topics covered in their work span sensor technology and measurement systems, electrical and bioimpedance tomography, advanced electrical measurement techniques, brain tumor detection and classification, EEG and brain-computer interfaces, advanced neural network applications, and analog and mixed-signal circuit design.

Salih Güneş has coauthored papers with several frequent collaborators. These include Mehmet Akif Erişmiş, Mehmet Demirtaş, Melahat Poyraz, Ahmet Kürşad Poyraz, and Yusuf Doğan.

The scientist's publications appear in varied venues such as Cognitive Neurodynamics, SN Applied Sciences, Elektronika ir Elektrotechnika, the 2020 Innovations in Intelligent Systems and Applications Conference (ASYU), and The Eurasia Proceedings of Science Technology Engineering and Mathematics.

Recent papers authored or coauthored by Salih Güneş include:

  • Analysis and design of a transimpedance amplifier based front-end circuit for capacitance measurements, 2020, SN Applied Sciences
  • BrainNeXt: novel lightweight CNN model for the automated detection of brain disorders using MRI images, 2025, Cognitive Neurodynamics
  • A Lossy Capacitance Measurement Circuit Based on Analog Lock-in Detection, 2020, Elektronika ir Elektrotechnika
  • Performance optimization of a Front-End Circuit for Capacitance Measurements using Grey Wolf Algorithm, 2020, 2020 Innovations in Intelligent Systems and Applications Conference (ASYU)
  • Implementation of an Augmented Reality Application for Basic Electrical Circuits, 2022, The Eurasia Proceedings of Science Technology Engineering and Mathematics

Best Publications

  • Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform

    Kemal Polat;Salih Güneş

  • An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease

    Kemal Polat;Salih Güneş

  • Breast cancer diagnosis using least square support vector machine

    Kemal Polat;Salih Güneş

  • A cascade learning system for classification of diabetes disease: Generalized Discriminant Analysis and Least Square Support Vector Machine

    Kemal Polat;Salih Güneş;Ahmet Arslan

  • A novel hybrid intelligent method based on C4.5 decision tree classifier and one-against-all approach for multi-class classification problems

    Kemal Polat;Salih Güneş

  • Efficient sleep stage recognition system based on EEG signal using k-means clustering based feature weighting

    Salih Güneş;Kemal Polat;Şebnem Yosunkaya

  • A new hybrid method based on fuzzy-artificial immune system and k-nn algorithm for breast cancer diagnosis

    Seral Şahan;Kemal Polat;Halife Kodaz;Salih Güneş

  • A new feature selection method on classification of medical datasets: Kernel F-score feature selection

    Kemal Polat;Salih Güneş

  • Detection of ECG Arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine

    Kemal Polat;Salih Güneş

  • Artificial immune recognition system with fuzzy resource allocation mechanism classifier, principal component analysis and FFT method based new hybrid automated identification system for classification of EEG signals

    Kemal Polat;Salih Güneş

  • Automatic detection of heart disease using an artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism and k-nn (nearest neighbour) based weighting preprocessing

    Kemal Polat;Seral Şahan;Salih Güneş

  • A new method to medical diagnosis: Artificial immune recognition system (AIRS) with fuzzy weighted pre-processing and application to ECG arrhythmia

    Kemal Polat;Seral Şahan;Salih Güneş

  • Diagnosis of heart disease using artificial immune recognition system and fuzzy weighted pre-processing

    Kemal Polat;Salih Güneş;Sülayman Tosun

  • A novel hybrid method based on artificial immune recognition system (AIRS) with fuzzy weighted pre-processing for thyroid disease diagnosis

    Kemal Polat;Seral Şahan;Salih Güneş

  • Breast cancer and liver disorders classification using artificial immune recognition system (AIRS) with performance evaluation by fuzzy resource allocation mechanism

    Kemal Polat;Seral Şahan;Halife Kodaz;Salih Güneş

  • Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease

    Halife Kodaz;Seral Özşen;Ahmet Arslan;Salih Güneş

  • A hybrid approach to medical decision support systems: Combining feature selection, fuzzy weighted pre-processing and AIRS

    Kemal Polat;Salih Güneş

  • The medical applications of attribute weighted artificial immune system (AWAIS): diagnosis of heart and diabetes diseases

    Seral Şahan;Kemal Polat;Halife Kodaz;Salih Güneş

  • Computer aided diagnosis of ECG data on the least square support vector machine

    Kemal Polat;Bayram Akdemir;Salih Güneş

  • Hepatitis disease diagnosis using a new hybrid system based on feature selection (FS) and artificial immune recognition system with fuzzy resource allocation

    Kemal Polat;Salih Güneş

Frequent Co-Authors

Kemal Polat
Kemal Polat Abant Izzet Baysal University

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