Bilgisayar Mühendisliği Bölümü Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/58

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Model based human face detection using skin color segmentation
(2002) Özbay, Eylem
Model Based Human Face Detection Using Skin Color Segmentation Özbay, Eylem Ms, Department of Computer Engineering Supervisor: Dr. Reza Hassanpour January 2005, 85 pages For identification of the people easiest way using the faces. However, it requires determining the location of the faces in the images. Face Identification systems are generally preceded by face segmentation systems. The main goal of thesis is locating the human faces and segmentation regions belonging to them using skin color segmentation methods and facial features such as nose, eyes, mouth etc. The segmentation results may be used as input to other related systems
Design and analysis of native XML databases in three-tier architectures
(2004) Ergen, Mehmet Tunç
XML is rapidly emerging as a standard for exchanging business data on the World Wide Web. From management systems to e-business application providers to pure development tools, XML has gone from newly underground technology to integrated component standard. It is used as the file format of choice for Web development, document interchange, and date interchange, and presents a new world of opportunities and challenges to programmers. It is predicted that by at the end of 2004, more than 75% of e-business applications will include XML regardless of which language the application has been written in. As more and more applications starts using XML there wilt be a need to efficiently handle the XML data at the back-end. The need to efficiently store and process XML documents has created the new XML supported technologies and tools. One of these tools is the Native XML Databases. It is based on document-in, document-out architecture with capabilities for storage, retrieval, querying and updating the documents. While Native XML Databases are an important new technology, they should not be used without careful analysis and consideration. In this thesis Native XML Databases are investigated and analyzed in a 3-tier architecture to gain and ensure several advantages that three-tier systems offer to application developers and information technology industry
Software implementation of I2C bus into Zilog MCU
(2004) Yüzbaşoğlu, Fırat
This study describes the design and implementation of multi-master software PC bus on Zilog's z8 microcontrollers. PC bus is developed to support a com- munication integrated circuits (ICs) and microcontrollers on the same board. The bus is expanded from a single board to separated desks. During the data transmission, a fully software handshaking provides a synchronization between two asynchronized microcontrollers. There are many PC hardware integrated chips in the market. On these chips, start of the transmission is detected by polling. An interrupt based hardware start detection is designed to prevent waste of time and resources in this work. Testing results show that transmis sion speed of software PC bus on Z8 microcontrollers is reached to the PC bus standards of Philips Semiconductors Co
Evaluation of terrain rendering algorithms
(2005) İnam, Emin
errain rendering plays an important role in outdoor virtual reality applications, games, Geographic Information System (GIS), military mission planning's and flight simulations, etc. Many of these applications require real-time dynamic interaction from end users and thus are required to rapidly process terrain data to adapt to user input. Typical height fields consist of a large number of polygons, so that even most high performance graphics computers have great difficulties to display even moderately sized height fields at interactive frame rates. The common solution is to reduce the complexity of the scene while maintaining a high image quality. This thesis is an evaluation of three real-time continuous terrain levels of detail algorithms described in the papers ROAMing Terrain: Real-time Optimally Adapting Meshes by Duchaineau, Real-Time Generation of Continuous Levels of Detail for Height Fields by Röttger and Fast Terrain Rendering Using Geometrical MipMapping by Willem H. de Boer. The evaluation and comparison of the algorithms is based on the trade- off of polygon count to terrain accuracy over separate test data sets. The main aim of this thesis is research on terrain rendering algorithms that is generate high quality image in real-time with using height data.
A computational analysis of a language structure in natural language text processing
(2005) Eş, Sinan
Text categorization or classification is a general task of classifying un-organized natural language texts according to specific subject matter or category. Electronic mail (e-mail) filtering is a binary text classification problem which the user emails can be classified as legitimate (non-spam) or un-wanted mail (spam). In this study, we tried to find a filtering solution that is able to automatically classify emails into spam and legitimate categories. In order to automatically and efficiently classify emails as spam or legitimate we took advantage of some Machine Learning methods and some novel ideas from Information Retrieval
Pattern recognition: Comparison study
(2005) Salim, Fawzı
Öne of the most important effects the field of Cognitive Science can have on the field of Computer Science is the development of technologies that make our tools more human. Evidenced by the fact that we are not currently ali using Tablet computers, accurate hand writing recognition is clearly a difficult problem to solve. Neural netvvorks field is interested with applications for many practices such as industrial process, marketing, medicine, business which is also relevant with hand writing recognition (our main study in this thesis). Hand writing recognition is an important field with applications in business 'form-filling1, including handwritten postal addresses, cheques, insurance applications, mail-order forms, tax returns, credit card sales slips, customs declarations and many others. These applications ali generale a handwritten script from an unconstrained population of writers and writing implements, which must subsequently be processed off-line by computer. To consider at the importance of neural networks and its applications, we used it in this research and we applied backpropagation algorithm to give us better results. We will present more details in the thesis especially in chapter four. The process of recognizing of handwriting from pixel information falls into a field of artificial iii l intelligence called pattern ör image recognition. Lots of work has been done in this field recently, and most techniques for pattern and image classifıcation make use of neural networks. This work implements neural networks in order to "learn" to recognize general features of hand vvritten digits using the well know backpropagation algorithm
Machine learning in artificial intelligence
(2006) Ercan, Tardu
In today’s world, learning is a process of computers as well as human being. “Learnable” systems and computers will become more important in following years and affect our lives in many ways. In this thesis, a survey has been carried out in the field of artificial intelligence, machine learning and especially on decision tree learning algorithms. Some of the decision tree learning algorithms was used to learn rules which are extracted from a dataset. The dataset which consists of water consumption of Ankara for one year and meteorological data of Ankara was used. The results indicate that which learning method is more efficient and have better performance.
Structural risk management of disasters
(2007) Battal, Fulya
In this thesis, an expert system that evaluates the risk of damage of buildings during an earthquake is studied. The system asks some critical questions about the ground type and structural properties of the buildings. The answers to these questions are evaluated to conclude on the risk of damage of the buildings and advise for the necessary precautions to decrease the damage of the building to the user. The rules and parameters are determined due to a predefined knowledgebase and utilized in the expert system called, Structural Risk Management of Disaster prepared by the software Exsys Corvid. This expert system may be used in determining the risk of damage of buildings including government buildings, hospitals, residences etc. The determination of the risk of damage is important to get ready for any possible earthquake
3D reconstruction of a scene using stereo images
(2008) Taşel, Faris Serdar
Two-dimensional photographs do not have depth-information. One solution to determine the location of an object in three-dimensional environment is to use more than one photograph as exposed by the nature. Extracting the depth information using stereo images is purposed in this thesis. The thesis analyzes the steps and encountered problems in three-dimensional reconstruction process, explains the solutions exposed with the aid of epipolar geometry using some of the feature-based matching techniques. Stereo images which are taken from two calibrated cameras viewing the same scene are used to obtain estimated three-dimensional data. Pinhole camera model, epipolar geometry and its recovery are discussed; common stereo triangulation methods are explained in the chapters of the thesis. Besides, feature extraction and matching topics which are used for the reconstruction process are examined. Some of the methods used in the thesis are presented by algorithmic solutions and mathematical notations. Significant advantages and disadvantages of the methods are briefly discussed and encountered problems are tried to be challenged by fundamental approaches.
Parallelization study on the clustering technique to mine large datasets
(2011) Yıldırım, Ahmet Artu
Parallel clustering algorithm implementations concerning message passing interface (MPI) and compute unified device architecture (CUDA) model with their applications to very large datasets have been presented in the thesis. WaveCluster is a novel clustering approach based on wavelet transforms. Despite it?s novelty, it requires considerable amount of time to collect results for large sizes of multidimensional datasets. In the MPI algorithm; divide and conquer approach has been followed and communication among processors are kept at minimum to achieve high efficiency. Developed parallel WaveCluster algorithm exposes high speedup and scales linearly with the increasing number of processors. Parallel behavior of WaveCluster approach has been also investigated by executing the algorithm on graphical processing unit (GPU). High speedup values have been obtained in the computation of wavelet transform and connected component labeling algorithms in the GPUs with respect to the sequential algorithms running on the CPU
Web services based real time data warehouse
(2012) Obalı, Murat
Today's business environment is quickly changing and business decision makers need for a historical picture of what happened and a picture of what was happening today. Traditional data warehouses provide a historical picture, but there is lack of fresh data. However, fresh data in data warehouses is a strong feature from the part of the users. The aim of this study is building a real time data warehouse using web services. First, we modelled both the conceptual and the logical design of real time data warehouse. For change data capture from source systems, we implemented web services based server and client software. Then, we used real time partition for real time data which is merged into data warehouse in a daily fashion. We, also, implemented a data integration service using query re-write approach to integrate data warehouse and real time partition data.
Finding the ethnical identity of human face
(2012) Yenice, Merve
In this thesis, how to find a human being’s ethnical identity from his/her face is analyzed. Parts of the face like eyes, nose, mouth, skin colour are used for defining the face. In addition to this, some programs like C# and Luxand are also used in correctly defining and calculating the facial parts. This calculation is very important and necessary in fractionating the human face and finding the dimensions of members of the face, because it gives the main idea about the shape, length and colour of face. The most important issues in determining and finding the ethnical identity of human face are shape, length and skin colour of the face. After finding these items the ethnical identity of a human can easily be found. The evidence found after working in this thesis is shown that the thesis has reached its aim willingly.
Integrating computer vision with a robot arm system
(2014) Yosif, Zead Mohammed
During last decades, robotic system has been employed in different fields, such as, industrial, civil, military, medical, and many other applications. Vision system is integrated with robot systems to enhance the controlling performance of the robot system. A great deal of features can be computed using the information have been gotten from vision sensors (camera). The extracted information from vision system can be used in the feedback to have the ability to control the robot armtor motion, but the operation of extracting this information from vision system is time consuming. This thesis addressed the problem of following (tracking) and grasping of moving target (object) with limited velocity in real time by employing the technology of Eyein- Hand, whereas a camera attached (mounted) to the robot arm end effector. This done by using a predictor (Kalman filter) that estimates the positions of the target in the future, an algorithm was designed to track an object move in different trajectories, within the camera field of view. The Kalman filter uses the measured position of the target as well as previous state estimates to fix the location of thetarget object at the next time step, in other word, the Kalman filter is applied to keep observing the object till grasp it. The employing of vision system information in the feedback control of the robot systems have been the major research in robotics and Mechatronic systems. The utilizing from this information has been proposed to handle stability and reliability issues in vision-based control system.
Multifunction robot controlled by computer vision system
(2014) Mustafa, Mohammed Sulaiman
In this thesis, we try to come up and build a robot platform with multifunction capabilities, easy to add, modify and delete those functions without redesigning, by using easy use technology that can create a suitable efficient platform. The process of building platform is by using figures, tables and programming code to make this thesis capable to apply and implement in real world, showing obstacles and challenges that lead to the key of success until it reaches the final goal. This thesis requires only basic level in electronic and computer programming because we are using a simplified way for building robot. The multifunction platform is a unique idea and opens new space to experimenters to get benefits from this opinions or ideas to use these functions in raw state, with no need to study hardware and software material of robot. The final robot form is shown in the last pages of this thesis as appendix
The observation of information security awareness in Turkey
(2014) Durmuş,Ahmet
In this thesis, information security awareness of five different sample domains has been examined by web-based general survey composed of basic security topics. Moreover, information security awareness of IT security personnel working in seven different public institutions which have great and complex network systems has also been examined by more technical survey as well. The correct and incorrect way of behaviour of respondents have been put forwarded in line with the discussion of information security principals by analyzing the responses with using well-known statistic analysis tool. Hence, the current posture of information security awareness has been spotted. The weak and strong sides of internet users in security knowledge have been emphasized with the analysis of general survey data. In the analysis of technical survey, the shortages of security measures resulted in some vulnerabilities in the institution networks have been highlighted. At the end of general survey, participants have been directed to relative website and a suggestion document has been also presented in order to contribute positively to their information security awareness at the same time.
An energy-efficient clustering based communication protocol with dividing the overall network area for wireless sensor networks
(2014) Khalaf, Abdulrahman Zaidan
In this thesis, the energy efficient and connectivity problem in wireless sensor networks (WSNs) is presented. There are more difference between energy levels of near nodes and far nodes of cluster heads. This problem compensated by dividing the entire network (sensor field) into equal area and applies different clustering policies to each section. The results compared with results of LEACH (Low Energy Adaptive Clustering Hierarchy). The performance of proposal system overcomed the previous studies. Also this protocol guaranted transmitting data and transmission in high traffic networks to reduce energy consumption and packet failure
An approach to improve the time complexity of dynamic provable data possession
(Çankaya Üniversitesi, 2016) Hawi, Mohammed Kadhim
In this thesis, we aim to take some actions for alleviating the fears when the data storage over outsourcing, and guarantee the integrity of the files in cloud computing. In this study, we have suggested some ideas to improve FlexDPDP scheme [13]. Particularly, proposed scheme successfully reduces the time complexity for verifying operations between the client and the server. The proposed scheme is a fully dynamic model. We involved some parameters to ensure the integrity of the metadata. In spite of the fact that auxiliary storage expenditure by Client-side (the client stores approximately 0.025% size of the raw file). The remarkable enhancement in this proposed scheme is reducing the complexity. The complexity of the communications and the computations decreased to O(1) in both Client-side and Server-side during the dynamically update (insertion, modification and deletion operations) and challenge operations.
Classification of diabetic retinopathy using pre-trained deep learning models
(2019) Al-Kamachy, Inas Mudheher Raghib Kafı
Diabetic Retinopathy (DR) is considered to be the first factor that leads to blindness. If it is not detected early, many people around the world would suffer from the diabetic disease that may lead to DR in their eyes. Any delay in regular monitoring and screening by ophthalmologists may cause rapid and dangerous progress of this disease which finally leads to human vision loss. The imbalance between the numbers of doctors required to monitor this disease and the number of patients around the world increasing year by year shows a major problem leading to poor regular monitoring and loss vision in many cases which could have been detected had there been good treatment in the earlier stages of DR. In order to solve this problem, serious aid was needed for a computer aid diagnosis (CAD). Deep learning pre-trained models are state-of-art in image recognition and image detection with good performance. In this research, we used image pre-processing and we built several convolution neural network models from scratch and fine-tuned five pre-trained deep learning models which used ImageNet as the dataset for medical images of diabetic retinopathy in order to classify diabetic retinopathy into five classes. After that, we selected the model that showed good performance to build a diabetic retinopathy web application using Flask as a framework web service. We used the KAGGLE kernel website with Jupyter as a notebook as well as Flask to build our web application. The final result of the AUC was 0.68 using InceptionResNetV2.
Determining rheumatoid arthritis and osteoarthritis diseases with plain hand x-rays using convolutional neural network
(2019) Üreten, Kemal
Recent advances in computer technology have facilitated the acquisition of high-resolution images and processing of images. Convolutional neural network (CNN) is a branch of deep learning. CNN was first introduced in 1995 by LeCun, and in 2012, AlexNet won the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC), after which there was rapid growth in deep learning applications. There are many successful studies using CNN especially in dermatology, pathology, radiology and ophthalmology. CNN highly successful in feature extraction and classification and requires less pre-processing. But in the CNN method, overfitting is an important problem that needs to be addressed and requires a large data set for training. If there is not enough data for CNN training from scratch, previously trained CNN network from the natural image data set are used for transfer learning. Transfer learning is the use of a pre-trained model for a new problem. In recent years, there have been a few studies showing that CNN models trained with natural images have achieved successful results in the medical field. Rheumatoid arthritis (RA) and hand osteoarthritis (OA) are two different diseases that cause pain, swelling, tenderness, loss of function in hand joints. In these diseases, affected joints and radiologic lesions show some differences. Treatment of both diseases is also different. Conventional plain hand X-Rays (CR) are often used to diagnosis, differential diagnosis of RA and OA. The aim of this study is to develop a software that will help physicians for differential diagnosis of RA and OA from CR. To the best our knowledge, this is the first study to distinguish between normal, hand OA and RA using plain hand radiographs. The efficiency of the created models was evaluated by using performance metrics such as accuracy, sensitivity, specificity and precision. In this study, pre-trained GoogLeNet, ResNet50 and VGG16 networks were used, transfer learning was applied. Successful results were obtained from all three pre-trained networks. In this study, data augmentation, droupout, fine tuning, learning rate decay was applied to prevent overfitting. And during the training, no signs of overfitting were observed in the training chart.
Prediction of the football match results with using machine learning algorithms
(2019) Çimen, Emre Altuğ
In this thesis, prediction results of the Spanish La Liga football matches were obtained by using three machine learning algorithms. The dataset includes four season match statistics and the results of these matches. In addition, this thesis investigated which performance parameters of the football game statistics affected the game results. Feature selection techniques were used to reduce the number of attributes. Three different classifiers which are artificial neural network, support vector machine and k- nearest neighborhood were used for prediction. Support vector machine classifier reached better results than the other classifiers when applied for the chosen fifteen attributes in the dataset.

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