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Yayın EEG signal compression based on classified signature and envelope vector sets(IEEE Computer Society, 2007) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaIn this paper, a novel method to compress ElectroEncephaloGram (EEG) Signal is proposed. The proposed method is based on the generation Classified Signature and Envelope Vector Sets (CSEVS) by using an effective k-means clustering algorithm. In this work on a frame basis, any EEG signal is modeled by multiplying three parameters as called the Classified Signature Vector, Classified Envelope Vector, and Frame-Scaling Coefficient. In this case, EEG signal for each frame is described in terms of the two indices R and K of CSEVS and the frame-scaling coefficient. The proposed method is assessed through the use of root-mean-square error (RMSE) and visual inspection measures. The proposed method achieves good compression ratios with low level reconstruction error while preserving diagnostic information in the reconstructed EEG signal.Yayın Real-time 3D inspection of large civil structures using a stereoscopic camera system equipped UAV(International Society for Photogrammetry and Remote Sensing, 2024-12-13) Akça, Devrim; Torkut, Çağın; Kemper, Gerhard; Kunz, Noah; Caner, Doğa; Gruen, ArminREALTIME3D is an innovative Mixed-Reality (MR) photogrammetry system that integrates photogrammetry, UAV technology, and VR/AR solutions to enable real-time 3D infrastructure inspection. By combining these technologies, the system allows users to remotely access, visualize, and measure 3D stereoscopic models in real time. An operator on-site pilots a UAV equipped with the stereo cameras, while experts, utilizing VR headsets, can observe and analyze the object of interest from remote locations. This approach enhances cost efficiency and safety during inspections of large-scale, critical structures. The paper introduces the first prototype of the system, detailing its hardware and software components.
