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In this work, eye pupil center estimation was performed by using Convolutional Neural Network (CNN) from deep learning methods which are mentioned frequently in the field of machine learning recently, without need for any special hardware. 64×64 image patches created with four different scales were trained through the Caffe framework using the AlexNet model, which was arranged according to its input...
Face recognition approaches that are based on deep convolutional neural networks (CNN) have been dominating the field. The performance improvements they have provided in the so called in-the-wild datasets are significant, however, their performance under image quality degradations have not been assessed, yet. This is particularly important, since in real-world face recognition applications, images...
In recent years, deep learning algorithm has been one of the most used method in machine learning. Success rate of the most popular machine learning problems has been increased by using it. In this work, we develop an eye detection method by using a deep neural network. The designed network, which is accepted as an input by Caffe, has 3 convolution layers and 3 max pooling layers. This model has been...
Off the shelf camera based eye pupil center detection has been very popular among computer vision community for the recent years. We propose an accurate and robust regressor based pupil center estimation method without any specialized hardware. The method trains a Support Vector Regressor using HOG features against the Euclidean distance between the center of the train patches and the ground-truth...
The operation of foreground background subtraction, which has a crucial role on video processing, needs to be processed in real time. In this paper, we present an implement of the pixel based adaptive segmentation (PBAS) algorithm on CUDA parallel programming platform to process high resolution videos in real time. The performance of the implementation is enhanced by using Nsight profiler metrics...
We concentrate on utilization of facial periocular region for biometric identification. Although this region has superior discriminative characteristics, as compared to mouth and nose, it has not been frequently used as an independent modality for personal identification. We employ a feature-based representation, where the associated periocular image is divided into left and right sides, and descriptor...
As one of the renewable energy sources, wind energy has received great attention in Turkey as in the rest of the world in the last decade. Despite of this trend, there is an increasing number of assessment reports stating the impact of wind farms on the performance degradation of electromagnetic propagation systems. In this paper, wind turbines' effects on radar detection performance are investigated...
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