Riries Rulaningtyas
- Media Technology top 5%
- Image Processing Techniques and Applications 17
- Biophysics top 5%
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- Digital Imaging for Blood Diseases 24
- Image Retrieval and Classification Techniques 6
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- COVID-19 diagnosis using AI 9
- Retinal Imaging and Analysis 7
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- Computer Science and Engineering 8
- AI in cancer detection 7
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- Medical Imaging and Analysis 5
Riries Rulaningtyas
63 papers receiving 356 citations
Peers
Comparison fields: 5 of 96
- Media Technology 85
- Biophysics 55
- Computer Vision and Pattern Recognition 119
- Neurology 30
- Radiology, Nuclear Medicine and Imaging 83
Countries citing papers authored by Riries Rulaningtyas
This map shows the geographic impact of Riries Rulaningtyas'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 Riries Rulaningtyas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riries Rulaningtyas more than expected).
Fields of papers citing papers by Riries Rulaningtyas
This network shows the impact of papers produced by Riries Rulaningtyas. 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 Riries Rulaningtyas. The network helps show where Riries Rulaningtyas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Riries Rulaningtyas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 7 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 1 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 1 | |
| 14 | 2023 | 0 | |
| 15 | 2022 | 0 | |
| 16 | 2021 | 1 | |
| 17 | 2020 | 10 | |
| 18 | 2020 | 5 | |
| 19 | 2018 | 8 | |
| 20 | The Improvement of Automatic Scanning Microscope Based on Intelligent Systems to Identify Mycobacterium Tuberculosis | 2014 | 1 |
About Riries Rulaningtyas
Riries Rulaningtyas is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 77 papers that have together received 372 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (24 papers), Image Processing Techniques and Applications (17 papers), COVID-19 diagnosis using AI (9 papers), Computer Science and Engineering (8 papers), Retinal Imaging and Analysis (7 papers), AI in cancer detection (7 papers), Image Retrieval and Classification Techniques (6 papers) and Medical Imaging and Analysis (5 papers). The work is most often cited by research in Media Technology (85 citations), Biophysics (55 citations), Computer Vision and Pattern Recognition (119 citations), Neurology (30 citations) and Radiology, Nuclear Medicine and Imaging (83 citations). Riries Rulaningtyas has collaborated with scholars based in Indonesia, Malaysia and Australia. Frequent co-authors include Andriyan Bayu Suksmono, Tati L. R. Mengko, Wahyudi Setiawan, Budi Dwi Satoto, Imas Sukaesih Sitanggang, Nur Chamidah, Tati Rajab Mengko, Alfian Pramudita Putra, Hong‐Seng Gan and Endah Purwanti. Their work appears in journals such as Studies in Informatics and Control, MethodsX, Symmetry, Applied Optics and Applied 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.