The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness... more
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to data-mine actual human behavior during drowsiness episodes. Auto-matic classifiers for 30 facial actions from the Facial Ac-tion Coding system were developed using machine learning on a separate database of spontaneous expressions. These facial actions include blinking and yawn motions, as well as a number of other facial movements. In addition, head motion was collected through automatic eye tracking and an accelerometer. These measures were passed to learning-based classifiers such as Adaboost and multinomial ridge regression. The system was able to predict sleep and crash episodes during a driving...
In this work an online handwritten text recognition system for Turkish has been developed using a Tablet PC as an interface. In recent years, although there has been great developments in the Tablet PC technology, still there are no... more
In this work an online handwritten text recognition system for Turkish has been developed using a Tablet PC as an interface. In recent years, although there has been great developments in the Tablet PC technology, still there are no applications for recognition in Turkish language. In this work, we have developed a prototype system using Hidden Markov Models which recognizes handwritten words from a small vocabulary list. This system has achieved a recognition rate over %90 percent.
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The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness... more
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to datamine actual human behavior during drowsiness episodes. Automatic classifiers for 30 facial actions from the Facial Action Coding system were developed using machine learning on a separate database of spontaneous expressions. These facial actions include blinking and yawn motions, as well as a number of other facial movements. In addition, head motion was collected through automatic eye tracking and an accelerometer. These measures were passed to learningbased classifiers such as Adaboost and multinomial ridge regression. The system was able to predict sleep and crash episodes during a driving com...
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Page 1. Tiirkqe Iqin Biiriinsel Yazidan K onupa Uretme A Prosodic Turkish Text-to-Speech Synthesizer Esra Viral, Kemal Oflazer ... Tiim an konu$mak ohyucu-nun sesinde degisme meydana getireeegi iqin fsrkli @ere yayllarak kaya... more
Page 1. Tiirkqe Iqin Biiriinsel Yazidan K onupa Uretme A Prosodic Turkish Text-to-Speech Synthesizer Esra Viral, Kemal Oflazer ... Tiim an konu$mak ohyucu-nun sesinde degisme meydana getireeegi iqin fsrkli @ere yayllarak kaya tamamlanml$hr. ...
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... vision based approaches detect driver drowsiness primarily by making pre-assumptions about the relevant behavior, focusing on blink rate, eye ... Sinyal işleme teknikleri ve makina öğrenme yontemleri kul-lanılarak kişi bağımsız ileri... more
... vision based approaches detect driver drowsiness primarily by making pre-assumptions about the relevant behavior, focusing on blink rate, eye ... Sinyal işleme teknikleri ve makina öğrenme yontemleri kul-lanılarak kişi bağımsız ileri derecede uykululuk sezim sistemi kurulmustur ...
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... Bir baska deyisle denekler arası deneyde, 30 saniyelik bir video kesidi verildi˘gi takdirde sis-tem uykulu ve uykusuz bölümleri 0.99 do ... sekilde en basarılı bes hareket birimi sırasıyla AU12 ( Dudak Kösesini Germe), AU7 (Göz... more
... Bir baska deyisle denekler arası deneyde, 30 saniyelik bir video kesidi verildi˘gi takdirde sis-tem uykulu ve uykusuz bölümleri 0.99 do ... sekilde en basarılı bes hareket birimi sırasıyla AU12 ( Dudak Kösesini Germe), AU7 (Göz Kapa˘gını Germe), AU4 (Kas ˙Indirme), AU26 (C¸ene ...