Dr. Yekta Said Can

Wissenschaftlicher Mitarbeiter
Lehrstuhl für Menschzentrierte Künstliche Intelligenz
Telefon: +49 821 598 2346
E-Mail:
Raum: 2041 (N)
Adresse: Universitätsstraße 6a, 86159 Augsburg

Research Interests

  • Wearable computing
  • Physiological Signal Processing
  • Machine learning
  • Stress Recognition
  • Document analysis
  • Social signal processing

Teaching

  • Deep Ubiquitous and Wearable Computing for Healthcare, University of Augsburg, Germany, Winter Semester 2022, Masters.
  • Wearable Technology Applications in Healthcare, University of Augsburg, Germany, Winter Semester 2022, Bachelors.
  • Principles of Artificial Intelligence, Bahcesehir University, Turkey, Winter Semester 2021, Masters.
 
 
 

Publication List

          

Journal Papers (Peer Reviewed)

 

  • Smart Affect Monitoring with Wearables in the Wild: An Unobtrusive Mood-Aware Emotion Recognition System, Can YS, Ersoy C., IEEE Transactions on Affective Computing, 2022.  doi: 10.1109/TAFFC.2022.3232483
  • Application level performance evaluation of wearable devices for stress classification with explainable AI, Chalabianloo N., Can YS, Umair M., Sas C., Ersoy C., Pervasive and Mobile  Computing 87, 101703
  • Ekiz D., Can YS and Ersoy C., ”Long Short-Term Memory Network Based Unobtrusive Workload Monitoring with Consumer Grade Smartwatches”, in IEEE Transactions on Affective  Computing, 2021. doi: 10.1109/TAFFC.2021.3110211.
  • Can YS, Gerrits PJ and Kabadayi ME, ”Automatic Detection of Road Types From the Third Military Mapping Survey of Austria-Hungary Historical Map Series With Deep Convolutional  Neural Networks,” in IEEE Access, vol. 9, pp. 62847-62856, 2021.
  • Can, YS “Stressed or Just Running? Differentiation of Mental Stress and Physical Activity by Using Machine Learning”. Turkish Journal of Electrical Engineering and Computer Science,  November 2021, https://doi.org/10.3906/elk-2102-138.
  • Ekiz D., Can YS, Dardağan YC, Aydar F., Kose RD and Ersoy C. , ”End-to-End Deep Multi- Modal Physiological Authentication With Smartbands,” in IEEE Sensors Journal, vol. 21, no.  13, pp. 14977-14986, 2021.
  • Can, YS and Ersoy, C., 2021. Privacy-preserving Federated Deep Learning for Wearable IoT- based Biomedical Monitoring. ACM Trans. Internet Technologies. 21, 1, Article 21, 2021.
  • Can, YS; Kabadayı, ME Automatic Estimation of Age Distributions from the First Ottoman Empire Population Register Series by Using Deep Learning. Electronics 2021, 10, 2253.
  • Can, YS, Kabadayi, ME Automatic CNN-Based Arabic Numeral Spotting and Handwritten Digit Recognition by Using Deep Transfer Learning in Ottoman Population Registers. appl.  science 2020, 10, 5430.
  • Can YS, Iles-Smith H, Chalabianloo N, Ekiz D, Fernandez-Alvarez J, Repetto C, ... Ersoy C (2020, June). How to Relax in Stressful Situations: A Smart Stress Reduction System. In  MDPI Healthcare (Vol. 8, No. 2, p. 100).
  • Can YS, Chalabianloo N, Ekiz D, Fernandez-Alvarez J, Repetto C, Riva G, ... Ersoy C (2020). Real-Life Stress Level Monitoring using Smart Bands in the Light of Contextual  Information. IEEE Sensors Journal.
  • Can YS, Gokay D, Kilic DR, Ekiz D, Chalabianloo N, Ersoy C (2020). How Laboratory Experiments Can Be Exploited for Monitoring Stress in the Wild: A Bridge Between Laboratory  and Daily Life. Sensors, 20(3), 838.
  • Can YS, Chalabianloo N, Ekiz D, Fernandez-Alvarez J, Riva G, Ersoy C (2020). Personal stress-level clustering and decision-level smoothing to enhance the performance of ambulatory stress detection with smartwatches. IEEE Access, 8, 38146-38163.
  • Can, YS, Arnrich, B, Ersoy, C (2019). Stress detection in daily life scenarios using smartphones and wearable sensors: A survey. Journal of biomedical informatics, 103139.
  • Can YS, Chalabianloo N, Ekiz D, Ersoy C (2019). Continuous Stress Detection Using  Wearable Sensors in Real Life: Programming Contest Case Study. Sensors, 19(8), 1849.

             

Conference Papers (Peer Reviewed)


 

  • YS Can, K. Büyükoğuz, EB Giritli, M. Şişik and F. Alagöz, ”Predicting Airfare Price Using Machine Learning Techniques: A Case Study for Turkish Touristic Cities,” 2022 30th Signal  Processing and Communications Applications Conference (SIU), Safranbolu, Turkey, pp. 1-4.
  • YS Can, H Erkut, EB Giritli, H Kutluay, K Büyükoğuz and C Demiroğlu, ”Developing Session-based Personalized Accommodation Recommender System by Using LSTM,” 2022 30th Signal Processing and Communications Applications Conference (SIU), Safranbolu , Turkey.
  • Can, YS, Erdem Kabadayi, M (2021, September). Text Detection and Recognition by using CNNs in the Austro-Hungarian Historical Military Mapping Survey. In The 6th International  Workshop on Historical Document Imaging and Processing (pp. 25-30).
  • Can, YS, Kabadayı, ME (2021, September). Line Segmentation of Individual Demographic Data from Arabic Handwritten Population Registers of Ottoman Empire. In Document Analysis and Recognition–ICDAR 2021
  • YS Can and M. Erdem Kabadayı, ”Curation of Historical Arabic Handwritten Digit Datasets from Ottoman Population Registers: A Deep Transfer Learning Case Study,” 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 2020, pp. 1853-1860.

 

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