Hasan Badem

588 citations
27 papers · 440 · h-index 12

Impact in

Papers in

Hasan Badem

23 papers receiving 413 citations

Peers

Hasan Badem
Comparison fields: 5 of 98
  • Artificial Intelligence 187
  • Health Information Management 25
  • Computer Vision and Pattern Recognition 99
  • Signal Processing 39
  • Media Technology 29
Replace Hong-Mo Je with:
Hong-Mo Je South Korea
Mehmet Emin Yüksel Türkiye
Son Vu Truong Dao Vietnam
Fitri Arnia Indonesia
M.R. Ito Canada
Benayad Nsiri Morocco
Jiaxu Leng China
Aiman Al-Sabaawi Australia
R. R. Sedamkar India
Maria Valueva Russia
Hasan Badem relative to Hong-Mo Je South Korea Hong-Mo Je's profile →
Citations per field
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Hong-Mo Je · 1×
Citations per year

Countries citing papers authored by Hasan Badem

Since Specialization
Citations

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

Fields of papers citing papers by Hasan Badem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Hasan Badem, 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 Hasan Badem Line = papers co-authored together Hasan Badem links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201794
2
DIAGNOSIS OF THE PARKINSON DISEASE BY USING DEEP NEURAL NETWORK CLASSIFIER
201754
3 201948
4 201744
5 201841
6 201821
7 201720
8 202019
9 202018
10 202016
11
Classification and diagnosis of the parkinson disease by stacked autoencoder
201613
12 201712
13 201611
14 20178
15 20195
16 20164
17 20232
18 20242
19 20192
20 20152

About Hasan Badem

Hasan Badem is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Physiology and Biomedical Engineering, having authored 27 papers that have together received 440 indexed citations. Recurring topics across this work include Neural Networks and Applications (5 papers), Voice and Speech Disorders (4 papers), Face and Expression Recognition (3 papers), Music and Audio Processing (3 papers), EEG and Brain-Computer Interfaces (3 papers), Metaheuristic Optimization Algorithms Research (3 papers), Muscle activation and electromyography studies (3 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (187 citations), Health Information Management (25 citations), Computer Vision and Pattern Recognition (99 citations), Signal Processing (39 citations) and Media Technology (29 citations). Hasan Badem has collaborated with scholars based in Türkiye and Saudi Arabia. Frequent co-authors include Abdullah Çalışkan, Alper Baştürk, Mehmet Emin Yüksel, Derviş Karaboğa, Selçuk Aslan, Zeynel Abidin Çil and Cem Sınanoğlu. Their work appears in journals such as Applied Soft Computing, Chinese Journal of Mechanical Engineering, Journal of Intelligent & Fuzzy Systems, IEEE Transactions on Fuzzy Systems and Engineering Applications of Artificial Intelligence.

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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