Muchallil Sayed

• Muchallil, Sayed; Ferdiansyah, Rahmat; Saddami, Khairun; Meutia, Ernita Dewi; Afnan, Afnan & Griwodz, Carsten (2026). Augmented Reality Implementation for Hijab Try-on Application. I Nasaruddin (Red.), 2025 3rd International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331578374. s. 272–276. doi: 10.1109/cosite68330.2025.11414287. Fulltekst i vitenarkiv Vis sammendrag

  Hijab is an obligatory clothing for Muslim women that has now developed into a fashion trend with various types such as Pashmina, Square, and Instant hijab. The growth of hijab business, primarily through e-commerce, presents a challenge for consumers to try and choose hijab online. This research aims to design an application that overcomes this problem by utilising Augmented Reality (AR) technology to visualise the appearance of consumers when wearing hijab, as well as the application of deep learning with MobileNetV1 architecture to classify the shape of consumers’ faces and provide appropriate hijab recommendations. The implementation results show that the face shape-based hijab recommendation system can perform classification well, where 76% of 25 respondents expressed satisfaction with the hijab recommendation results. The AR-based virtual try-on feature also provides a satisfying hijab trying-on experience, with 76% of respondents feeling satisfied. Overall, 84% of respondents stated that the app helped them shop for hijab online. This finding shows the app’s potential to enhance the virtual hijab shopping experience.

• Muchallil, Sayed; Kaifan, Malika Atifa; Azhary, Mulkan; Fitria, Maya; Nurdin, Yudha & Griwodz, Carsten (2026). Rethinking Cardiac Anatomy Learning with Markerless AR: A Design and Usability Evaluation. I Tahir, Nooritawati Md. (Red.), 2026 22nd IEEE International Colloquium on Signal Processing & Its Applications (CSPA). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331569129. s. 472–477. doi: 10.1109/cspa68262.2026.11517875. Fulltekst i vitenarkiv Vis sammendrag

  Medical education requires a deep understanding of complex physiological systems, particularly cardiac anatomy. Conventional media often lack the interactive 3D visualization necessary for spatial comprehension. While Augmented Reality (AR) offers immersive solutions, existing applications heavily rely on physical markers, limiting flexibility. This study presents HeartAR, a markerless AR application utilizing ground plane detection to facilitate interactive, self-directed exploration of 3D cardiac models. Developed through a Human-Centered Design framework, the system integrates multi-axis rotation, anatomical labeling, and dynamic heartbeat simulations.We evaluated the system’s usability with medical students using task-based observations and the System Usability Scale (SUS).The evaluation yielded an SUS score of 79.75, indicating a high level of usability and user acceptability. The core contribution of this work lies in the practical implementation and usability validation of markerless spatial tracking for specific anatomical modules, providing foundation for accessible, outside-the-classroom medical training tools.

• Muchallil, Sayed; Halnunm, Konrad & Griwodz, Carsten (2021). Low-latency head-tracking for Augmented Reality. I Saddami, Khairun; Fitria, Maya & Bahri, Al (Red.), 2021 International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665425094. s. 192–197. doi: 10.1109/COSITE52651.2021.9649619. Fulltekst i vitenarkiv
• Hansen, Henry Haugsten; Muchallil, Sayed; Griwodz, Carsten; Sillerud, Vetle & Johanssen, Fredrik (2020). Dense LIDAR point clouds from room-scale scans. I Alay, Özgü & Toni, Laura (Red.), MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference. Association for Computing Machinery (ACM). ISSN 9781450368452. s. 88–98. doi: 10.1145/3339825.3391862. Fulltekst i vitenarkiv

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