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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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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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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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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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Monitoring of Miner by RF Signal

SARAY, Tuğba | ÇETİNKAYA, Ali | MENDİ, Engin

Wireless communication technology is spreading rapidly to all areas of our lives. The technology, which has a wide range of applications from radios, intelligent home systems, automation applications to GPS units, was used in monitoring the workers working in mines in this study. Most of the mining area underground mining is risky and the possibility of accident (gas jams, the explosion and dents, etc.) is the area of high. Locating is vital in this line of work when a sudden accident or dent occurred in which the worker will be known and the position of the recovery efforts can be intensified ...Daha fazlası

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New Approaches Based on Real and Complex Forms of Ripplet-I Transform for Image Analysis

YAŞAR, Hüseyin | CEYLAN, Murat

The multi resolution analysis are important parts of image processing. Curvelet transform is analysis method which have been using wide variety of applications in multi resolution analysis. Ripplet-I transform is defined by recently generalising of the curvelet transform by adding parameters support (c) and degree (d). Even though this transform has been found out recently, it has been using wide variety of applications. Fast discrete and complex fast discrete versions of ripplet-I transform were examined by this study. In denoising application, better results were obtained with fast discrete ...Daha fazlası

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A Novel Method and Mobile System for Accurate Heart Rate Measurement from Finger and Face

GÖNÜLTAŞ, Emre | DEMİRBAŞÇI, Oğuz | MENDİ, Engin

Heart rate is an important vital indicator which provides information about the rhythm of the heart and helps in diagnosing several heart diseases. As it can be usually determined manually, there are also some medical devices that automatically measure heart rate. Measuring heart rate quickly and consistently may play important role in the early detection of heart attack and various heart rate related disorders. In this work, a mobile based system that performs quick and practical heart rate measurement. Processing RGB color changes in the image frames recorded from finger or face, which canno ...Daha fazlası

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A Systematic Circular Weight Initialisation of Kohonen Neural Network for Travelling Salesman Problem

MUHAMMED, Jawad | ALTUN, Halis

Self-organising neural networks have since been employed by researchers in solving the travelling salesman problem. However, with these networks, the final tour length as well as the convergence time, largely depends on the initial weights of the networks. In this paper, systematic initialisation of Kohonen neural network weight in a circle is presented, that involves randomly initialising the weights to be along a circular path, with centroid equals the centroid of all the cities. Our major contribution is on having the circle exhibit different radius on each test run, in order to effectively ...Daha fazlası

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