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Conference Object Citation - Scopus: 1Comparison of Target Detection Performance for Radiance and Reflectance Domain in Vnir Hyperspectral Images(Institute of Electrical and Electronics Engineers Inc., 2019) Ozdil,O.; Gunes,A.; Esin,Y.E.; Demirel,B.; Ozturk,S.In this paper, the hyperspectral detection of targets in visible-near infrared (VNIR) images is studied. The change of radiance domain signatures in images taken in different locations, time and altitudes are analyzed. A new radiance domain detection scheme for VNIR images under 1000 m altitude is proposed. The analysis shows that the radiance domain signatures of each target, that are collected from an image taken at 10 m altitude, can be effectively used for pure pixel target detection in other VNIR images taken at altitudes between 10 - 1000 m. The proposed approach is tested using several target types and on images taken at different altitudes and environmental conditions. Our results show that target detection in radiance domain provides a cheaper, easier and effective alternative to reflectance domain, in VNIR images. © 2019 IEEE.Conference Object Citation - Scopus: 1Multiple Underwater Target Bearing Tracking Using Member Filter;(Institute of Electrical and Electronics Engineers Inc., 2018) Gunes,A.; Guldogan,M.B.Underwater acoustic vector sensors (AVS) are devices which can measure scalar pressure and three dimensional acceleration or particle velocity with only one sensor. By using these four measurements, target detection and tracking is possible. In case multiple targets exist, multi-target detection and tracking methods must be applied. Because these methods are more general, the algorithms are more involved and complex. In this framework, multi-target multi-Bernoulli (MeMBer) is a promising filter based on random finite sets (RFS) for multi-target tracking problems. In this work, for the first time in the literature, MeMBer filter is analyzed using a single underwater acoustic vector sensor in a scenario including two targets. Simulation results indicate that MeMBer filter can successfully track the targets. © 2018 IEEE.Conference Object Shape Recognition With Low Cost Sensors;(Institute of Electrical and Electronics Engineers Inc., 2018) Saloglu,K.; Hosafci,A.; Birbilen,M.; Bulut,Y.A.; Gunes,A.This paper proposes a method to recognize the shape of some objects that have different geometrical properties using an infra-red sensor. To that end, a mechanism that has two degrees of freedom is designed. Scanning of the different objects are obtained. Noise on scanning output is removed. Finally, all the outputs for different objects are discussed to obtain the specifications to do shape recognition. © 2018 IEEE.
