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In this study, a system with reinforcement learning for push-pull mesh based video streaming applications running over p2p networks is designed. In push-pull based video streaming systems, each node in the system may receive video data from more than one parent. In the proposed system, a node which started to receive insufficient video data from any parent selects a new parent with a probabilistic...
The aim of this work is to perform polyphonic music transcription in an efficient way. The problem is formulated as a linear model and the speed is improved by a randomized SVD-based method. The method is shown to compete with the best resulting approaches in literature. The conventional methods seem to fail in this era of big data whereas the proposed method efficiently handles this by use of randomized...
In this paper a new filter structure is proposed for the H∞ estimation under delayed measurements for continuous time processes. As an example, target tracking problem is considered and results obtained from the classical H2-optimal and the proposed H∞-optimal filters are compared.
In this paper, we proposed a passive stereo system that for obtain 3-D faces under standard diffused light sources in a single-shot. The system ensures to obtain high quality 3-D models in sub-millimeter accurate. The proposed system consists of three 5Mp cameras and two diffused standard light sources and also the system is designed to allow to increase the number of cameras. Technically the system...
In this study, the effects of bending on propagation losses of the proposed hexagonal shaped photonic crystal fiber has been investigated by employing the full vectorial finite element method. Bending loss analysis of 60 air hole PCF over wide wavelength range has been reported. Also, the effect of air hole diameters and the bending radius on the propagation loss of the fundamental mode has been investigated.
Graphs are important mathematical tools for modelling processes. An important issue in this area is to infer the changes that occur in the underlying generative process. In this work, inference of multiple change points in stochastic block graph time series is studied. A well-known algorithm for inference in time series is the forward-backward algorithm. In order to decrease computational complexity...
In this work, an online three-dimensional profile measurement systems in order to determine reasons, internal tensions etc., which affect tyre uniformity, balance and performance has been developed. Measurement system that was developed consists of two line laser and two cameras. Three dimensional model of the tyre profile has been reconstructed by projection of the line laser onto the tyre surface...
Human action recognition is a topic of increasing interest in recent years. Most of the work is focused on actions that have simple, periodic structure such as walking, running and hugging, but our everyday life contains very different types of actions with challenging problems. Space-time interest points and the bag of words approach have been shown a good performance on action recognition. For more...
Undetectable fractures and misdiagnosis are the most important problems in orthopaedics field. In recent years, researchers have studied on enhancing of diagnosis success with “Computer Aided Diagnosis” systems. In this study, “Artificial neural network (ANN) based automatic bone fracture detection system” has been performed taking into consideration mentioned needs. In this proposed system, firstly,...
Magnetic resonance imaging provides diffusion weighted images (DMRI), which non-invasively reconstruct the brain white matter pathways. DMRI is used to study brain white matter diseases as well as aid surgical planning. As localization of different white matter pathways surrounding a pathology is crucial for surgical planning, automatic extraction and classification of different anatomical white matter...
With the increase in the resolution and the amount of satellite images, automatic extraction of urban areas and buildings became more important in the past decade. Extracting such information manually is tedious and needs a lot of expert effort. In this work, a system for detecting the urban areas, then finding the buildings inside these areas is proposed. LISA analysis is used for detection of urban...
Matrix-based (2D) methods have advantages over vector-based (1D) methods. Matrix-based methods generally have less computational costs and higher recognition performances with respect to vector-based variants. In this work a two dimensional variation of Discriminative Common Vector Approach (2D-DCVA) is implemented. The performance of the method in single image problem is compared with the one dimensional...
This paper considers a two-way amplify-and-forward (AF) relay network. Two source nodes exchange messages during two time slots via a half-duplex relay node. We aim to minimize system total power by constraining source nodes' received signal-to-noise ratios (SNR), thus, satisfying the minimum quality of service (QoS). By solving the optimization problem composed for this case, closed form expressions...
In this study, a new handwritten character recognition system able to work for a large-scale data set, faster and have a high recognition rates, is developed. For this purpose this study is implemented within four stages which are pre-processing, feature selection, classification and speedup. Two-dimensional wavelet-based method and the Sobel gradient method are used for the feature extraction process...
Space-Time Adaptive Processing (STAP) has been widely used in spaceborne and airborne radar platforms in order to track ground moving targets. In this study, a generic STAP radar model, wideband jammer signal model and ground clutter model are implemented in simulation environment. The implemented models are used to demonstrate the coverage area analysis of the respective radar systems which employs...
In this work, the curve compression problem is approached with a model-based probabilistic framework. We propose three different models. The proposed models can be used for purposes such as feature extraction or compression. The first model we propose is basically a Bayesian regression model for fitting piece-wise defined segments. The second model unifies clustering with regression. The third model...
Systems of infrared remote sensing can be successful as far as they distinguish the target from the background. Modeling of sea backgound has a great importance for the systems of sensing and the counter systems developed to protect the platforms on the sea surface. It is known that sea surface is one of the most strongly polarized media in infrared band. In this paper modeling of the polarization...
As an alternative technique to well-known constant modulus algorithm (CMA), a Decision Feedback Equalizer via Channel Matched Filter (CMF-DFE) based blind channel estimation and equalization algorithm is proposed in this paper. The proposed technique employs Particle Swarm Optimization (PSO) in training, where the conventional CMA and least mean squares (LMS) based training algorithms are found slow...
In this paper we consider segmentation of inhomogeneous foreground and background images using nonparametric shape priors. Non-homogeneity of foreground and background regions of objects to be segmented complicates the process of segmentation. Low quality of images and noise can be considered as reasons of this problem. Furthermore these regions themselves can be textured. One approach proposed for...
In the recent studies image segmentation and object recognition are handled cooperatively. Majority of those studies employ supervised or semi-supervised training by providing labels. However, providing labeling is too laborious. For this reason, we propose using prior knowledge on domain information instead of class labels. Given the domain knowledge the system detects domain invariants in the image...
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