Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Erdem Akagunduz"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 7589-7604 (2022)
Forests can be efficiently monitored by automatic semantic segmentation of trees using satellite and/or aerial images. Still, several challenges can make the problem difficult, including the varying spectral signature of different trees, lack of suff
Externí odkaz:
https://doaj.org/article/32290d4c2d5548aa958fd8537763cc65
Autor:
Oguzhan Cifdaloz, Erdem Akagunduz
Publikováno v:
Neural Computing and Applications. 33:16745-16757
In this paper, we investigate the parameter identification problem in dynamical systems through a deep learning approach. Focusing mainly on second-order, linear time-invariant dynamical systems, the topic of damping factor identification is studied.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e818e9cc983543476ed8493faf2ed54
https://doi.org/10.1007/s00521-021-06271-5
https://doi.org/10.1007/s00521-021-06271-5
Atmospheric turbulence has a degrading effect on the image quality of long-range observation systems. As a result of various elements such as temperature, wind velocity, humidity, etc., turbulence is characterized by random fluctuations in the refrac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab2138bec99f5bb9410cc9990300abab
Publikováno v:
INISTA
In this study, we aim at designing a smart glove, which consists of different inertial sensors and an EMG sensor and developing a human-machine interaction application by pre-processing and fusing these different sensory data. We also aim at providin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c304f4d00cda051de84a49651e9261a
https://doi.org/10.1109/inista52262.2021.9548472
https://doi.org/10.1109/inista52262.2021.9548472
Publikováno v:
SIU
In this study, a spectrogram based false color representation of earthquake accelergrams is proposed and its usability for both human investigation and its application in convolutional networks are discussed. By using more than forty two thousand ear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1d15370508d642c19638aa642cbe93f
https://doi.org/10.1109/siu49456.2020.9302312
https://doi.org/10.1109/siu49456.2020.9302312
Publikováno v:
SIU
Convolutional Neural Networks can solve the target detection problem satisfactorily. However, the proposed solutions generally require deep networks and hence, are inefficient when it comes to utilising them on performance-limited systems. In this pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a12c95c8e0b4adf92035ff05ca1c102
https://doi.org/10.1109/siu49456.2020.9302501
https://doi.org/10.1109/siu49456.2020.9302501
Memorability of an image is a characteristic determined by the human observers' ability to remember images they have seen. Yet recent work on image memorability defines it as an intrinsic property that can be obtained independent of the observer. {Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38421b9586880862d09e6a20a872f8d8
https://eprints.whiterose.ac.uk/145732/1/PRE_TPAMI_Defining_Image_Memorability_using_the_Visual_Memory_Schema_1_.pdf
https://eprints.whiterose.ac.uk/145732/1/PRE_TPAMI_Defining_Image_Memorability_using_the_Visual_Memory_Schema_1_.pdf
Autor:
H. Seckin Demir, Erdem Akagunduz
Publikováno v:
Volume: 28, Issue: 1 302-317
Turkish Journal of Electrical Engineering and Computer Science
Turkish Journal of Electrical Engineering and Computer Science
In this paper, we introduce a machine learning approach to the problem of infrared small target detection filter design. For this purpose, similar to a convolutional layer of a neural network, the normalized-cross-correlational NCC layer, which we ut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96472ab120be9100d506f4173dcdac09
http://arxiv.org/abs/2006.08162
http://arxiv.org/abs/2006.08162
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 21:756-763
A novel method to detect human falls in depth videos is presented in this paper. A fast and robust shape sequence descriptor, namely the Silhouette Orientation Volume (SOV), is used to represent actions and classify falls. The SOV descriptor provides
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4525d832996b24799195a6c81e43f490
https://doi.org/10.1109/jbhi.2016.2570300
https://doi.org/10.1109/jbhi.2016.2570300
Publikováno v:
ICMV
Hyper-spectral satellite imagery, consisting of multiple visible or infrared bands, is extremely dense and weighty for deep operations. Regarding problems related to vegetation as, more specifically, tree segmentation, it is difficult to train deep a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d0b6e2e640696e2033f3eb8af340536
https://doi.org/10.1117/12.2556374
https://doi.org/10.1117/12.2556374