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| |SINTA | | |SINTA |
| |https://sinta.kemdikbud.go.id/authors/profile/6977579 | | |https://sinta.kemdikbud.go.id/authors/profile/6977579 |
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| == Expertise ==
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| * Deep Learning
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| * Artificial Intelligence
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| * Computer Vision
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| * Machine Learning
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| == International Journal indexed by Scopus/WoS ==
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| *[https://www.sciencedirect.com/science/article/pii/S2590005625001225 Optimizing spinal cord lesion segmentation using hierarchical classification and U-NET based segmentation model. ''Electronic'' (2025)]
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| *[http://dx.doi.org/10.1007/s00586-024-08464-7 A deep learning approach for cervical cord injury severitydetermination through axial and sagittal magnetic resonance imagingsegmentation and classification (PDF) A deep learning approach for cervical cord injury severity determination through axial and sagittal magnetic resonance imaging segmentation and classification. Available from: https://www.researchgate.net/publication/383526135_A_deep_learning_approach_for_cervical_cord_injury_severity_determination_through_axial_and_sagittal_magnetic. ''European Spine Journal'' (2024)]
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| *[https://ieeexplore.ieee.org/document/10636887 SpinalAI: A Deep Learning Approach to Predict Vertebrae-Column Level, Structure, and Foraminal on Cervical Spine Axial MRI Images. ''ICiCos'' (2024)]
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| == National Journal indexed by Sinta ==
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| *[https://jurnal.stts.edu/index.php/INSYST/article/view/438 A Hierarchical Multi-Label Classification Approach for the Automated Interpretation of Spinal MRI Series. ''Insyst : Journal of Intelligent System and Computation'' (2025)]
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| == Formal Educations ==
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| {| class="wikitable"
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| !Year
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| !Level
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| !School/Institution/University
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| |-
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| |2012
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| |S1
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| |Institut Sains dan Teknologi terpadu Surabaya
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| |-
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| |2022
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| |S2
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| |Institut Sains dan Teknologi terpadu Surabaya
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| |} | | |} |
Latest revision as of 22:01, 21 February 2026
Rudi Limantara, S.Kom., M.Kom., CDSS.
Rudi holds a Bachelor’s degree in Informatics from Sekolah Tinggi Teknik Surabaya and a Master’s degree in Computer Science from Institut Sains dan Teknologi Terpadu Surabaya, graduating Summa Cumlaude. He specializes in Computer Vision, Digital Image Processing, Artificial Intelligence, and Deep Learning. Currently, Rudi is actively involved in medical research using Deep Learning technologies, collaborating with hospitals across Indonesia. As an educator, he teaches various courses including Programming Algorithms, Databases, Object-Oriented Programming, Computer Vision, Digital Image Processing, Computer Graphics, Artificial Intelligence, Deep Learning, and Machine Learning. Rudi is a member of the International Association of Engineers (IAENG), reinforcing his commitment to academic excellence and professional development in the technology field.
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