Browsing by Author "Türetken, Engin"

Now showing items 1-6 of 6

    • Adaptation of MobileNetV2 for Face Detection on Ultra-Low Power Platform 

      Narduzzi, Simon; Türetken, Engin; Thiran, Jean-Philippe; Dunbar, L. Andrea (2022-06)
      Designing Deep Neural Networks (DNNs) running on edge hardware remains a challenge. Standard designs have been adopted by the community to facilitate the deployment of Neural Network models. However, not much emphasis is ...

    • Efficient Neural Vision Systems Based on Convolutional Image Acquisition 

      Pad, Pedram; Narduzzi, Simon; Kündig, Clément; Türetken, Engin; Bigdeli, Siavash A.; Dunbar, L. Andrea (2020-06-14)
      Despite the substantial progress made in deep learning in recent years, advanced approaches remain computationally intensive. The trade-off between accuracy and computation time and energy limits their use in real-time ...

    • Embedded Deep Learning for Sleep Staging 

      Türetken, Engin; Van Zaen, Jerome; Delgado-Gonzalo, Ricard (2019)
      The rapidly-advancing technology of deep learning (DL) into the world of the Internet of Things (IoT) has not fully entered in the fields of m-Health yet. Among the main reasons are the high computational demands of DL ...

    • Multi-modal driver drowsiness detection: A feasibility study 

      Lemkaddem, Alia; Delgado-Gonzalo, Ricard; Türetken, Engin; Dasen, Stephan; Moser, Virginie; Gressum, Carl; Sola, Josep; Ferrario, Damien; Verjus, Christophe (2018)
      Driver drowsiness is a significant contributing factor to road accidents and can lead to severe physical injuries, deaths, and significant economic losses. Earlier research primarily concentrated on estimating the level ...

    • Real Time Eye Gaze Tracking for Human Machine Interaction in the Cockpit 

      Türetken, Engin; Saeedi, Sareh; Bigdeli, Siavash; Stadelmann, Patrick; Cantale, Nicolas; Lutnyk, Luis; Raubal, Martin; Dunbar, L. Andrea (2022-03-02)
      The Aeronautics industry has pioneered safety from digital checklists to moving maps that improve pilot situational awareness and support safe ground movements. Today, pilots deal with increasingly complex cockpit environments ...

    • Sleep Staging Using Deep Neural Networks 

      Braun, Fabian; Renevey, Philippe; Van Zaen, Jérôme; Lemkaddem, Alia; Türetken, Engin; Dunbar, Andrea; Delgado-Gonzalo, Ricard; Lemay, Mathieu; De Jaegere, Kurt; Horvath, Christian M.; Roth Wälti, Corinne; Brill, Anne-Kathrin; Ott, Sebastian R. (2019-10)
      Polysomnography (PSG) is the current state of the art for sleep staging but has several drawbacks: it requires a multitude of sensors and needs experienced technicians, which makes it expensive. It is further not suited ...