Changes and progresses in information technologies have played an important role in the development of intelligent vehicle systems in recent years. Driver fatigue is an important factor in vehicle accidents. For this reason, traffic accidents involving driver fatigue and driver carelessness have been followed by researchers. In this article, a Multi-tasking Convulational Neural Network (ConNN *) model is proposed to detect driver drowsiness/fatigue. Eye and mouth characteristics are utilized for driver's behavior model. Changes to these characteristics are used to monitor driver fatigue. With the proposed Multi-task ConNN model, unlike the studies in the literature, both mouth and eye information are classified into a single model at the same time. Driver fatigue is determined by calculating eyes' closure duration/Percentage of eye closure (PERCLOS) and yawning frequency/frequency of mouth (FOM). In this study, the fatigue degree of the driver is divided into 3 classes. The proposed model achieved 98.81% fatigue detection on YawdDD and NthuDDD dataset. The success of the model is presented comparatively. INDEX TERMS Convolutional neural network, driver fatigue detection, PERCLOS, FOM. * Convulational Neural Network has been abbreviated as ConNN, not CNN or CoNN, CNN has been used as the abbreviation of Celluar Neural Network and CoNN has been used as the abbreviation of Cooperative neural networks in the leterature as a long time. The associate editor coordinating the review of this manuscript and approving it for publication was Zahid Akhtar .

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Özetçe-Bu çalışmada Eliptik Eğri Kriptografisi (ECC) üzerinde Koblitz Metodu kullanılarak video dosyaları içine EnÖnemsiz Bit (LSB) tabanlı bilgi gizlenmesi amaçlanmıştır. Alıcıya iletilmek istenen mesaj ASCII karakterlerine dönüştürüldükten sonra, tek indise sahip karakterler Koblitz Metoduyla şifrelenerek (x,y) ikilileri elde edilir ve bu ikililerin koordinat noktalarını ifade ettiği varsayılır. Tek indise sahip bu noktaların ilgili frame üzerindeki piksel değeri, kendinden sonra gelen çift indisli ASCII karakterin ikilik tabandaki değeri ile LSB metoduyla değiştirilir. Mesajın tüm karakterleri için aynı işlem tekrarlandıktan sonra mesaj video frameleri içine gizlenmiş olur. Anahtar Kelimeler -Video Steganografi; Steganografi; Kriptografi; Koblitz Metod; LSB; Eliptik Eğri Kriptografisi, Video İşleme, İmge İşleme.Abstract-In this work we aimed to Least Significant Bit (LSB) based information hiding over video files using Koblitz's Method over Elliptic Curve Cryptography. After which the message to be sent to the recipient converted into ASCII characters, single index characters are encrypted by Koblitz's Method, (x,y) pairs obtained, and it is assumed that these pairs (x,y) express as a coordinate points. The pixel value on the relevant frame of single index points replaced with next double index ASCII character's binary value using LSB method. After repeating the same process for all characters in the message, the message is hidden into the video frames.