Now showing items 1-11 of 11

    • Covariance matrix-based fire and flame detection method in video 

      Habiboğlu, Y. H.; Günay, O.; Çetin, A. E. (Springer, 2011-09-17)
      This paper proposes a video-based fire detection system which uses color, spatial and temporal information. The system divides the video into spatio-temporal blocks and uses covariance-based features extracted from these ...
    • Feature extraction and classification in a two-state brain-computer interface 

      Altindis, F.; Yilmaz, B. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Brain Computer Interface (BCI) technology is used to help patients who do not have control over motor neurons such as ALS or paralyzed patients, to communicate with outer world. This work aims to classify motor imageries ...
    • Flame detection method in video using covariance descriptors 

      Habiboǧlu, Y.H.; Günay O.; Çetin, A.E. (2011)
      Video fire detection system which uses a spatio-temporal covariance matrix of video data is proposed. This system divides the video into spatio-temporal blocks and computes covariance features extracted from these blocks ...
    • Human activity recognition with different artificial neural network based classifiers 

      Catalbas B.; Morgul, O. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Human Activity Recognition is a popular topic of research, with the importance it carries and its limited feature vector, to reach high success rates because of the difficulty faced in classification. With the increase of ...
    • Image feature extraction using compressive sensing 

      Eleyan, A.; Kose, K.; Cetin, A.E. (Springer Verlag, 2014)
      In this paper a new approach for image feature extraction is presented. We used the Compressive Sensing (CS) concept to generate the measurement matrix. The new measurement matrix is different from the measurement matrices ...
    • Investigation of personal variations in activity recognition using miniature inertial sensors and magnetometers 

      Yurtman, Aras; Barshan, Billur (IEEE, 2012-04)
      In this paper, data acquired from five sensory units mounted on the human body, each containing a tri-axial accelerometer, gyroscope, and magnetometer, during 19 different human activities is used to calculate inter-subject ...
    • Mel-cepstral methods for image feature extraction 

      Çakir, S.; ÇEtin, A.E. (2010)
      A feature extraction method based on two-dimensional (2D) mel-cepstrum is introduced. The concept of one-dimensional (1D) mel-cepstrum which is widely used in speech recognition is extended to 2D in this article. Feature ...
    • Nearest-neighbor based metric functions for indoor scene recognition 

      Cakir, F.; Güdükbay U.; Ulusoy, Ö. (Academic Press, 2011)
      Indoor scene recognition is a challenging problem in the classical scene recognition domain due to the severe intra-class variations and inter-class similarities of man-made indoor structures. State-of-the-art scene ...
    • Pulse doppler radar target recognition using a two-stage SVM procedure 

      Eryildirim, A.; Onaran, I. (IEEE, 2010-07-07)
      It is possible to detect and classify moving and stationary targets using ground surveillance pulse-Doppler radars (PDRs). A two-stage support vector machine (SVM) based target classification scheme is described here. The ...
    • Wavelet based flame detection using differential PIR sensors 

      Erden F.; Töreyin, B.U.; Soyer, E.B.; Inaç I.; Günay O.; Köse, K.; Çetin, A.E. (2012)
      In this paper, a flame detection system using a differential Pyro-electric Infrared (PIR) sensor is proposed. A differential PIR sensor is only sensitive to sudden temperature variations within its viewing range and it ...
    • Word retrieval in Ottoman documents 

      Arifoǧlu, D.; Duygulu, P. (2011)
      In this paper, two image matching methods are adapted to retrieve words in Ottoman documents. The first method is based on Dynamic Time Warping (DTW) method proposed in [7], while the second method is based on the Shape ...