Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima

O. G. Sezer; A. Erçil; M. Keskinöz

doi:10.1109/SIU.2005.1567629

Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima

O. G. Sezer^*
, A. Erçil
, M. Keskinöz

^*Bu çalışma için yazışmadan sorumlu yazar

Sabanci University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

1 Atıf (Scopus)

Özet

In this paper, we propose an object recognition technique using higher order statistics without the combinatorial explosion of time and memory complexity. The proposed technique is a fusion of two popular algorithms in the literature, Independent Component Analysis (ICA) and Support Vector Machines (SVM). We propose to use ICA to reduce the redundancy in the images and obtain some feature vectors for every image which has lower dimensions and then make use of SVM to classify these feature vectors coming from the ICA step. Experimental results are shown for Coil-20 and an internally created database of 2D manufacturing objects.

Tercüme edilen katkı başlığı	Independent component based 3D object recognition using support vector machines
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Sayfalar	99-102
Sayfa sayısı	4
DOI'lar	https://doi.org/10.1109/SIU.2005.1567629
Yayın durumu	Yayınlandı - 2005
Harici olarak yayınlandı	Evet
Etkinlik	IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 - Kayseri, Turkey Süre: 16 May 2005 → 18 May 2005

Yayın serisi

Adı	Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Hacim	2005

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Ülke/Bölge	Turkey
Şehir	Kayseri
Periyot	16/05/05 → 18/05/05

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 9 Sanayi, Yenilikçilik ve Altyapı

Belgeye Erişim

10.1109/SIU.2005.1567629

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Sezer, O. G., Erçil, A., & Keskinöz, M. (2005). Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima. In Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 (pp. 99-102). Makale 1567629 (Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005; Hac. 2005). https://doi.org/10.1109/SIU.2005.1567629

@inproceedings{bfdf1562563f4567bb34410685cb6650,

title = "Destek vekt{\"o}r makinesi kullanarak baǧimsiz bile{\c s}en tabanli 3B nesne tanima",

abstract = "In this paper, we propose an object recognition technique using higher order statistics without the combinatorial explosion of time and memory complexity. The proposed technique is a fusion of two popular algorithms in the literature, Independent Component Analysis (ICA) and Support Vector Machines (SVM). We propose to use ICA to reduce the redundancy in the images and obtain some feature vectors for every image which has lower dimensions and then make use of SVM to classify these feature vectors coming from the ICA step. Experimental results are shown for Coil-20 and an internally created database of 2D manufacturing objects.",

author = "Sezer, \{O. G.\} and A. Er{\c c}il and M. Keskin{\"o}z",

year = "2005",

doi = "10.1109/SIU.2005.1567629",

language = "T{\"u}rk{\c c}e",

isbn = "0780392396",

series = "Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005",

pages = "99--102",

booktitle = "Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005",

note = "IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 ; Conference date: 16-05-2005 Through 18-05-2005",

}

Sezer, OG, Erçil, A & Keskinöz, M 2005, Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima. in Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005., 1567629, Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005, hac. 2005, pp. 99-102, IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005, Kayseri, Turkey, 16/05/05. https://doi.org/10.1109/SIU.2005.1567629

Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima. / Sezer, O. G.; Erçil, A.; Keskinöz, M.
Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005. 2005. p. 99-102 1567629 (Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005; Hac. 2005).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima

AU - Sezer, O. G.

AU - Erçil, A.

AU - Keskinöz, M.

PY - 2005

Y1 - 2005

N2 - In this paper, we propose an object recognition technique using higher order statistics without the combinatorial explosion of time and memory complexity. The proposed technique is a fusion of two popular algorithms in the literature, Independent Component Analysis (ICA) and Support Vector Machines (SVM). We propose to use ICA to reduce the redundancy in the images and obtain some feature vectors for every image which has lower dimensions and then make use of SVM to classify these feature vectors coming from the ICA step. Experimental results are shown for Coil-20 and an internally created database of 2D manufacturing objects.

AB - In this paper, we propose an object recognition technique using higher order statistics without the combinatorial explosion of time and memory complexity. The proposed technique is a fusion of two popular algorithms in the literature, Independent Component Analysis (ICA) and Support Vector Machines (SVM). We propose to use ICA to reduce the redundancy in the images and obtain some feature vectors for every image which has lower dimensions and then make use of SVM to classify these feature vectors coming from the ICA step. Experimental results are shown for Coil-20 and an internally created database of 2D manufacturing objects.

UR - https://www.scopus.com/pages/publications/33846565474

U2 - 10.1109/SIU.2005.1567629

DO - 10.1109/SIU.2005.1567629

M3 - Konferans katkısı

AN - SCOPUS:33846565474

SN - 0780392396

SN - 9780780392397

T3 - Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005

SP - 99

EP - 102

BT - Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005

T2 - IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005

Y2 - 16 May 2005 through 18 May 2005

ER -

Sezer OG, Erçil A, Keskinöz M. Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima. In Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005. 2005. p. 99-102. 1567629. (Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005). doi: 10.1109/SIU.2005.1567629

Destek vektör makinesi kullanarak baǧimsiz bileşen tabanli 3B nesne tanima

Özet

Yayın serisi

???event.eventtypes.event.conference???

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap