Publications

2024

Sepanosian, T., & Durmaz Incel, O. (2024, October). Boxing Gesture Recognition in Real-Time using Earable IMUs. In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 673-678).
Sepanosian, T., & Durmaz Incel, O. (2024, October). Training Smarter with OpenEarable: A Boxing Gesture Recognition Dashboard Integration. In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 921-924).
Agac, S., & Incel, O. D. (2024). Resource-efficient, sensor-based human activity recognition with lightweight deep models boosted with attention. Computers and Electrical Engineering, 117, 109274.
Saylam, B., & İncel, Ö. D. (2024). Multitask Learning for Mental Health: Depression, Anxiety, Stress (DAS) Using Wearables. Diagnostics, 14(5), 501.
Agac, S., & Incel, O. D. (2024, June). Boosting the Performance of Lightweight HAR Models with Attention and Knowledge Distillation. In 2024 International Conference on Intelligent Environments (IE) (pp. 1-8). IEEE.
Yıldırım, A., & İncel, Ö. D. (2024, May). Class-Incremental Continual Learning for Human Activity Recognition with Motion Sensors. In 2024 32nd Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.

Agac, S., & Durmaz Incel, O. (2023). User Authentication and Identification on Smart Glasses with Motion Sensors. Springer SN Computer Science (accepted)
Bursa, S. Ö., Durmaz İncel, Ö., & Işıklar Alptekin, G. (2023). Building Lightweight Deep learning Models with TensorFlow Lite for Human Activity Recognition on Mobile Devices. Annals of Telecommunications, 1-16.
Bursa, S. O., Incel, O. D., & Alptekin, G. I. (2023). Personalized and motion-based human activity recognition with transfer learning and compressed deep learning models. Computers and Electrical Engineering, 109, 108777.
Agac, S., & Durmaz Incel, O. (2023). On the Use of a Convolutional Block Attention Module in Deep Learning-Based Human Activity Recognition with Motion Sensors. Diagnostics, 13(11), 1861.
Kilic, O., Saylam, B., & Durmaz Incel, O. (2023, March). Sleep Quality Prediction from Wearables using Convolution Neural Networks and Ensemble Learning. In Proceedings of the 2023 8th International Conference on Machine Learning Technologies (pp. 116-120).
Incel, O. D., & Bursa, S. O. (2023). On-Device Deep Learning for Mobile and Wearable Sensing Applications: A Review. IEEE Sensors Journal.

Full list of publications available at Google Scholar Page