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Improved license plate detection using HOG-based features and genetic algorithm

MUHAMMAD, Jawad | ALTUN, Halis

In this paper, a new improved plate detection method which uses genetic algorithm (GA) is proposed. GA randomly scans an input image using a fixed detection window repeatedly, until a region with the highest evaluation score is obtained. The performance of the genetic algorithm is evaluated based on the area coverage of pixels in an input image. It was found that the GA can cover up to 90% of the input image in just less than an average of 50 iterations using 30×130 detection window size, with 20 population members per iteration. Furthermore, the algorithm was tested on a database that contain ...Daha fazlası

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A New Method For Extraction Of Image's Features: Complex Discrete Ripplet-II Transform

YAŞAR, Hüseyin | CEYLAN, Murat

Wavelet transform extracts the features of a signal and image via shifting and weighting methods. This transform has either advantages or disadvantages on image processing applications. One of important disadvantage of wavelet transform is limited orientation problem. This problem has been solved by different orientation with ridgelet transform. Ripplet-II transform is defined by recently generalising of the ridgelet transform by adding parameter degree (d). Complex discrete form of ripplet-II transform defined by this study and added to the literature. Also, complex discrete Ripplet-II transf ...Daha fazlası

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A Hybrid Asymmetric Traffic Classifier For Deep Packet Inspection Systems With Route Asymmetry

ÖZTOPRAK, Kasım | YAZICI, Mehmet Akif

A flow is said to be asymmetrically routed if its packets follow separate paths for forward and reverse directions. Routing asymmetry leads to problems in flow identification, policy enforcement, quota management, traffic shaping etc. in DPI systems. There are two existing approaches to battle routing asymmetry: clustering and state sharing. The latter fails with stateless traffic, while clustering leads to large traffic overhead. We propose the Hybrid Asymmetric Traffic Classifier (HATC) method that merges the best aspects of the two existing methods. HATC is able to handle all types of asymm ...Daha fazlası

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SpEnD portal: Linked data discovery using SPARQL endpoints

YUMUŞAK, Semih | ARAS, Rıza Emre | UYSAL, Elif | DOĞDU, Erdoğan | KODAZ, Halife | ÖZTOPRAK, Kasım

We present the project SpEnD, a complete SPARQL endpoint discovery and analysis portal. In a previous study, the SPARQL endpoint discovery and analysis steps of the SpEnD system were explained in detail. In the SpEnD portal, the SPARQL endpoints are extracted from the web by using web crawling techniques, monitored and analyzed by live querying the endpoints systematically. After many sustainability improvements in the SpEnD project, the SpEnD system is now online as a portal. SpEnD portal currently serves 1487 SPARQL endpoints, out of which 911 endpoints are uniquely found by SpEnD only when ...Daha fazlası

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Early autism diagnosis of children with machine learning algorithms

BÜYÜOFLAZ, Fatiha Nur | ÖZTÜRK, Ali

Autism Spectrum Disorder (ASD) is a neuro-developmental disorder that has become one of the major health problems, and early diagnosis has a great deal of important in terms of controlling the disease. The increase in the number of autoimmune influenza and ASD cases in the world reveals an urgent need to develop easily applied and effective screening methods In this study, performance comparisons were made using three different classification methods, Naive Bayes, IBk (k-nearest neighbors), RBFN (radial basis function network), and Random Forest, on UCI 2017 Autistic Spectrum Disorder Screenin ...Daha fazlası

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Neuro-fuzzy Classification of Transcranial Doppler Signals with Chaotic Meaures and Spectral Parameters

ÖZTÜRK, Ali | ARSLAN, Ahmet

Transcranial Doppler (TCD) is a non-invasive diagnosis method which is used in diagnosis of various brain diseases by measuring the blood flow velocities in brain arteries. In this study, chaos analysis of the TCD signals recorded from the middle arteries of the temporal region of brain of the 82 patients and 23 healthy people was investigated. Among 82 patients, 20 of them had cerebral aneurism, 10 had brain hemorrhage, 22 had cerebral oedema and the remaining 30 had brain tumor. Maximum Lyapunov exponent which is the strongest quantitative indicator of chaos was found to be positive for all ...Daha fazlası

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Comparison of machine learning algorithms on different datasets

UYSAL, Elif | ÖZTÜRK, Ali

Machine learning algorithms are methods used to classify data. Aim of this study is comparison of machine learning algorithms on different datasets. For this study, 9 different machine learning algorithms with 10 fold cross validation method in WEKA is classified on 3 different datasets. As a result of classification, machine learning algorithm which has high accuracy rate is different for 3 datasets. Multilayer Perceptron algorithm for Car Evaluation dataset, Random Forest algorithm for Image Segmentation dataset and Simple Logistic algorithm for User Knowledge Modeling dataset were obtained. ...Daha fazlası

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Topic Distribution Constant Diameter Overlay Design Algorithm (TD-CD-ODA)

ÖZTOPRAK, Kasım | LAYAZALI, Sina | DOĞDU, Erdoğan

Publish/subscribe communication systems, where nodes subscribe to many different topics of interest, are becoming increasingly more common in application domains such as social networks, Internet of Things, etc. Designing overlay networks that connect the nodes subscribed to each distinct topic is hence a fundamental problem in these systems. For scalability and efficiency, it is important to keep the maximum node degree of the overlay in the publish/subscribe system low. Ideally one would like to be able not only to keep the maximum node degree of the overlay low, but also to ensure that the ...Daha fazlası

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Real-Time Resistor Color Code Recognition using Image Processing in Mobile Devices

DEMİR, Muhammed Fatih | ÇANKIRLI, Ayşenur | KARABATAK, Begüm | YAVARIABDI, Amir | MENDİ, Engin | KUSETOĞULLARI, Hüseyin

This paper proposes a real-time video analysis algorithm to read the resistance value of a resistor using a color recognition technique. To achieve this, firstly, a nonlinear filtering is applied to input video frame to smooth intensity variations and remove impulse noises. After that, a photometric invariants technique is employed to transfer the video frame from RGB color space to Hue-Saturation-Value (HSV) color space, which decreases sensitivity of the proposed method to illumination changes. Next, a region of interest is defined to automatically detect resistor's colors and then an Euclid ...Daha fazlası

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Statistical analysis of 3D-printed flat GRIN lenses

AÇIKGÖZ, Hulusi | ARYA, Ravi Kumar | MITTRA, Raj

This paper presents the statistical analysis of a 3D printed flat lens by using the Polynomial Chaos Expansion (PCE) analysis technique. The flat lens is fabricated using the 3D printing technology and is based on the grading-index (GRIN) approach. It is composed of several concentric rings with graded relative permittivity, made of a single material with different air holes-host material volume ratio. We show that the hole size can have significant effect on the performance of the lens, especially on the focal distance. PCE analysis enables us also to determine the impact of each individual r ...Daha fazlası

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Self-Adaptive Hybrid PSO-GA Method for Change Detection Under Varying Contrast Conditions in Satellite Images

KUSETOĞULLARI, Hüseyin | YAVARIABDI, Amir

This paper proposes a new unsupervised satellite change detection method, which is robust to illumination changes. To achieve this, firstly, a preprocessing strategy is used to remove illumination artifacts and results in less false detection than traditional threshold-based algorithms. Then, we use the corrected input data to define a new fitness function based on the difference image. The purpose of using Self-Adaptive Hybrid Particle Swarm Optimization-Genetic Algorithm (SAPSOGA) is to combine two meta-heuristic optimization algorithms to search and find the feasible solution in the NP-hard ...Daha fazlası

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Short term prediction of aluminium strip thickness via Support Vector Machines

ÖZTÜRK, Ali | ŞEHERLİ, Rıfat

The fundamental principle of cold rolling process is the tension produced by the coiling and uncoiling motors of the rolling machine. If the tension is not properly regulated, the strip thickness will not be homogenous over the surface and even ruptures may occur. Therefore, short-term prediction of the aluminium strip thickness is important to control the tension. In this study, nonlinear time series analysis methods were applied to the recorded thickness data in order to obtain the embedding vectors with appropriate embedding dimension and time delay. For various prediction horizons, the emb ...Daha fazlası

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