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Toplam kayıt 15, listelenen: 1-10
Sequential Forward Feature Selection for Facial Expression Recognition
(IEEE, 2016)
Facial expression recognition is an important computer vision problem with various applications. In this study, we investigate the effectiveness of features derived from facial landmarks in facial expression recognition. ...
HEp-2 Cell Classification using a Deep Neural Network Trained for Natural Image Classification
(IEEE, 2016)
Deep convolutional neural networks is a recently developed method that yields very successful results in image classification. Deep neural networks, which have a high number of parameters, require a large amount of data ...
Sequential forward feature selection for facial expression recognition [Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi]
(Institute of Electrical and Electronics Engineers Inc., 2016)
Facial expression recognition is an important computer vision problem with various applications. In this study, we investigate the effectiveness of features derived from facial landmarks in facial expression recognition. ...
HEp-2 cell classification using a deep neural network trained for natural image classification [Dogal Imge Siniflandirmak için Egitilmis bir Derin Sinir Agi ile HEp-2 Hücresi Siniflandirilmasi]
(Institute of Electrical and Electronics Engineers Inc., 2016)
Deep convolutional neural networks is a recently developed method that yields very successful results in image classification. Deep neural networks, which have a high number of parameters, require a large amount of data ...
Visualization of power lines recognized in aerial images using deep learning [Havadan alinan görüntülerde derin ögrenme ile taninan güç hatlarinin görsell?stirilmesi]
(Institute of Electrical and Electronics Engineers Inc., 2018)
Aerial power lines used to conduct electrical energy pose a significant risk of accidents for aerial vehicles. In this study, we propose a method to highlight the power lines in an aerial image. The visual feedback provided ...
Quantification of Projective Distortion for Fiducial Markers
(IEEE, 2013)
The aim of this study is to quantify the projective distortion of candidate quadrilaterals found in a square-framed fiducial marker detection algorithm. Based on the quantified value, candidates can be eliminated in such ...
Realtime circular object detection based on the statistical compactness estimation [İstati·sti·ksel tikizlik kesti·ri·mi·ne dayali gerçek zamanli dai·resel nesne tespi·ti·]
(2012)
Gathering statistical and geometrical information by processing the shape contours is the common way of feature extraction on object detection and recognition studies. Compactness is an important shape descriptor which ...
Quantification of projective distortion for fiducial markers [Duzlemsel dsaretciler dcin dzdusumsel carpikligin nicelendirilmesi]
(2013)
The aim of this study is to quantify the projective distortion of candidate quadrilaterals found in a square-framed fiducial marker detection algorithm. Based on the quantified value, candidates can be eliminated in such ...
Correcting writing errors in turkish with a character-level neural language model [Dahi anlamindaki de ayri yazilir: Türkçe yazim hatalarinin karakter-seviyeli bir sinirsel dil modeli ile düzeltilmesi]
(Institute of Electrical and Electronics Engineers Inc., 2018)
A large part of the written content on the Internet is composed of social media posts, articles written for content platforms and user comments. In contrast to the content prepared for print media, these types of texts ...
Coin recognition based on geometric features [Geometrik Öznitelik Tabanli Madeni Para Tanima]
(Institute of Electrical and Electronics Engineers Inc., 2015)
In this study, it is aimed to count the total amount in an image of coins using machine vision methods. The extrinsic parameters of the camera whose intrinsic parameters are already known are estimated relative to the plane ...