Search results for: Classification algorithms
1123 Fault Zone Detection on Advanced Series Compensated Transmission Line using Discrete Wavelet Transform and SVM
Authors: Renju Gangadharan, G. N. Pillai, Indra Gupta
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In this paper a novel method for finding the fault zone on a Thyristor Controlled Series Capacitor (TCSC) incorporated transmission line is presented. The method makes use of the Support Vector Machine (SVM), used in the classification mode to distinguish between the zones, before or after the TCSC. The use of Discrete Wavelet Transform is made to prepare the features which would be given as the input to the SVM. This method was tested on a 400 kV, 50 Hz, 300 Km transmission line and the results were highly accurate.Keywords: Flexible ac transmission system (FACTS), thyristorcontrolled series-capacitor (TCSC), discrete wavelet transforms(DWT), support vector machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17231122 Auto Regressive Tree Modeling for Parametric Optimization in Fuzzy Logic Control System
Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao
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The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13821121 An Improved Genetic Algorithm to Solve the Traveling Salesman Problem
Authors: Omar M. Sallabi, Younis El-Haddad
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The Genetic Algorithm (GA) is one of the most important methods used to solve many combinatorial optimization problems. Therefore, many researchers have tried to improve the GA by using different methods and operations in order to find the optimal solution within reasonable time. This paper proposes an improved GA (IGA), where the new crossover operation, population reformulates operation, multi mutation operation, partial local optimal mutation operation, and rearrangement operation are used to solve the Traveling Salesman Problem. The proposed IGA was then compared with three GAs, which use different crossover operations and mutations. The results of this comparison show that the IGA can achieve better results for the solutions in a faster time.
Keywords: AI, Genetic algorithms, TSP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26041120 An Advanced Method for Speech Recognition
Authors: Meysam Mohamad pour, Fardad Farokhi
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In this paper in consideration of each available techniques deficiencies for speech recognition, an advanced method is presented that-s able to classify speech signals with the high accuracy (98%) at the minimum time. In the presented method, first, the recorded signal is preprocessed that this section includes denoising with Mels Frequency Cepstral Analysis and feature extraction using discrete wavelet transform (DWT) coefficients; Then these features are fed to Multilayer Perceptron (MLP) network for classification. Finally, after training of neural network effective features are selected with UTA algorithm.Keywords: Multilayer perceptron (MLP) neural network, Discrete Wavelet Transform (DWT) , Mels Scale Frequency Filter , UTA algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23441119 Real-Time Digital Oscilloscope Implementation in 90nm CMOS Technology FPGA
Authors: Nasir Mehmood, Jens Ogniewski, Vinodh Ravinath
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This paper describes the design of a real-time audiorange digital oscilloscope and its implementation in 90nm CMOS FPGA platform. The design consists of sample and hold circuits, A/D conversion, audio and video processing, on-chip RAM, clock generation and control logic. The design of internal blocks and modules in 90nm devices in an FPGA is elaborated. Also the key features and their implementation algorithms are presented. Finally, the timing waveforms and simulation results are put forward.Keywords: CMOS, VLSI, Oscilloscope, Field Programmable Gate Array (FPGA), VHDL, Video Graphics Array (VGA)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30741118 GA based Optimal Sizing and Placement of Distributed Generation for Loss Minimization
Authors: Deependra Singh, Devender Singh, K. S. Verma
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This paper addresses a novel technique for placement of distributed generation (DG) in electric power systems. A GA based approach for sizing and placement of DG keeping in view of system power loss minimization in different loading conditions is explained. Minimal system power loss is obtained under voltage and line loading constraints. Proposed strategy is applied to power distribution systems and its effectiveness is verified through simulation results on 16, 37-bus and 75-bus test systems.
Keywords: Distributed generation (DG), Genetic algorithms (GA), optimal sizing and placement, Power loss.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34521117 Meteorological Data Study and Forecasting Using Particle Swarm Optimization Algorithm
Authors: S. Esfandeh, M. Sedighizadeh
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Weather systems use enormously complex combinations of numerical tools for study and forecasting. Unfortunately, due to phenomena in the world climate, such as the greenhouse effect, classical models may become insufficient mostly because they lack adaptation. Therefore, the weather forecast problem is matched for heuristic approaches, such as Evolutionary Algorithms. Experimentation with heuristic methods like Particle Swarm Optimization (PSO) algorithm can lead to the development of new insights or promising models that can be fine tuned with more focused techniques. This paper describes a PSO approach for analysis and prediction of data and provides experimental results of the aforementioned method on realworld meteorological time series.Keywords: Weather, Climate, PSO, Prediction, Meteorological
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20651116 Use of Hierarchical Temporal Memory Algorithm in Heart Attack Detection
Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi
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In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.Keywords: HTM, Real time anomaly detection, ECG, Cardiac Anomalies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7801115 A Modified AES Based Algorithm for Image Encryption
Authors: M. Zeghid, M. Machhout, L. Khriji, A. Baganne, R. Tourki
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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. In this paper, we analyze the Advanced Encryption Standard (AES), and we add a key stream generator (A5/1, W7) to AES to ensure improving the encryption performance; mainly for images characterised by reduced entropy. The implementation of both techniques has been realized for experimental purposes. Detailed results in terms of security analysis and implementation are given. Comparative study with traditional encryption algorithms is shown the superiority of the modified algorithm.Keywords: Cryptography, Encryption, Advanced EncryptionStandard (AES), ECB mode, statistical analysis, key streamgenerator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 50361114 Metaheuristics Methods (GA and ACO) for Minimizing the Length of Freeman Chain Code from Handwritten Isolated Characters
Authors: Dewi Nasien, Habibollah Haron, Siti SophiayatiYuhaniz
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This paper presents a comparison of metaheuristic algorithms, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), in producing freeman chain code (FCC). The main problem in representing characters using FCC is the length of the FCC depends on the starting points. Isolated characters, especially the upper-case characters, usually have branches that make the traversing process difficult. The study in FCC construction using one continuous route has not been widely explored. This is our motivation to use the population-based metaheuristics. The experimental result shows that the route length using GA is better than ACO, however, ACO is better in computation time than GA.Keywords: Handwriting Recognition, Feature Extraction, Freeman Chain Code, Genetic Algorithm and Ant ColonyOptimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20501113 Advanced Convolutional Neural Network Paradigms-Comparison of VGG16 with Resnet50 in Crime Detection
Authors: Taiwo. M. Akinmuyisitan, John Cosmas
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This paper practically demonstrates the theories and concepts of an Advanced Convolutional Neural Network in the design and development of a scalable artificial intelligence model for the detection of criminal masterminds. The technique uses machine vision algorithms to compute the facial characteristics of suspects and classify actors as criminal or non-criminal faces. The paper proceeds further to compare the results of the error accuracy of two popular custom convolutional pre-trained networks, VGG16 and Resnet50. The result shows that VGG16 is probably more efficient than ResNet50 for the dataset we used.
Keywords: Artificial intelligence, convolutional neural networks, Resnet50, VGG16.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2261112 Trajectory Estimation and Control of Vehicle using Neuro-Fuzzy Technique
Authors: B. Selma, S. Chouraqui
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Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in controlling the non linear system.
Keywords: Adaptive neuro-fuzzy inference system (ANFIS), Fuzzy logic, neural network, nonlinear system, control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17731111 Granulation using Clustering and Rough Set Theory and its Tree Representation
Authors: Girish Kumar Singh, Sonajharia Minz
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Granular computing deals with representation of information in the form of some aggregates and related methods for transformation and analysis for problem solving. A granulation scheme based on clustering and Rough Set Theory is presented with focus on structured conceptualization of information has been presented in this paper. Experiments for the proposed method on four labeled data exhibit good result with reference to classification problem. The proposed granulation technique is semi-supervised imbibing global as well as local information granulation. To represent the results of the attribute oriented granulation a tree structure is proposed in this paper.Keywords: Granular computing, clustering, Rough sets, datamining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17101110 Multimodal Biometric Authentication Using Choquet Integral and Genetic Algorithm
Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara
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The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.
Keywords: Multimodal biometrics, data fusion, Choquet integral, fuzzy measures, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25101109 The Locker Problem with Empty Lockers
Authors: David Avis, Luc Devroye, Kazuo Iwama
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We consider a cooperative game played by n players against a referee. The players names are randomly distributed among n lockers, with one name per locker. Each player can open up to half the lockers and each player must find his name. Once the game starts the players may not communicate. It has been previously shown that, quite surprisingly, an optimal strategy exists for which the success probability is never worse than 1 − ln 2 ≈ 0.306. In this paper we consider an extension where the number of lockers is greater than the number of players, so that some lockers are empty. We show that the players may still win with positive probability even if there are a constant k number of empty lockers. We show that for each fixed probability p, there is a constant c so that the players can win with probability at least p if they are allowed to open cn lockers.
Keywords: Locker problem, pointer-following algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12861108 An Overview of Construction and Demolition Waste as Coarse Aggregate in Concrete
Authors: S. R. Shamili, J. Karthikeyan
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Fast development of the total populace and far and wide urbanization has surprisingly expanded the advancement of the construction industry. As a result of these activities, old structures are being demolished to make new buildings. Due to these large-scale demolitions, a huge amount of debris is generated all over the world, which results in a landfill. The use of construction and demolition waste as landfill causes groundwater contamination, which is hazardous. Using construction and demolition waste as aggregate can reduce the use of natural aggregates and the problem of mining. The objective of this study is to provide a detailed overview on how the construction and demolition waste material has been used as aggregate in structural concrete. In this study, the preparation, classification, and composition of construction and demolition wastes are also discussed.
Keywords: Aggregate, construction and demolition waste, landfill, large scale demolition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6221107 Denoising based on Wavelets and Deblurring via Self-Organizing Map for Synthetic Aperture Radar Images
Authors: Mario Mastriani
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This work deals with unsupervised image deblurring. We present a new deblurring procedure on images provided by lowresolution synthetic aperture radar (SAR) or simply by multimedia in presence of multiplicative (speckle) or additive noise, respectively. The method we propose is defined as a two-step process. First, we use an original technique for noise reduction in wavelet domain. Then, the learning of a Kohonen self-organizing map (SOM) is performed directly on the denoised image to take out it the blur. This technique has been successfully applied to real SAR images, and the simulation results are presented to demonstrate the effectiveness of the proposed algorithms.Keywords: Blur, Kohonen self-organizing map, noise, speckle, synthetic aperture radar.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17211106 A New Evolutionary Algorithm for Cluster Analysis
Authors: B.Bahmani Firouzi, T. Niknam, M. Nayeripour
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Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Keywords: Data clustering, Hybrid evolutionary optimization algorithm, K-means algorithm, Simulated Annealing (SA), Particle Swarm Optimization (PSO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22681105 Weighted k-Nearest-Neighbor Techniques for High Throughput Screening Data
Authors: Kozak K, M. Kozak, K. Stapor
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The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.
Keywords: biological screening, kernel methods, KNN, QSAR
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22581104 MovieReco: A Recommendation System
Authors: Dipankaj G Medhi, Juri Dakua
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Recommender Systems act as personalized decision guides, aiding users in decisions on matters related to personal taste. Most previous research on Recommender Systems has focused on the statistical accuracy of the algorithms driving the systems, with no emphasis on the trustworthiness of the user. RS depends on information provided by different users to gather its knowledge. We believe, if a large group of users provide wrong information it will not be possible for the RS to arrive in an accurate conclusion. The system described in this paper introduce the concept of Testing the knowledge of user to filter out these “bad users". This paper emphasizes on the mechanism used to provide robust and effective recommendation.Keywords: Collaborative Filtering, Content Based Filtering, Intelligent Agent, Level of Interest, Recommendation System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16351103 On-Road Text Detection Platform for Driver Assistance Systems
Authors: Guezouli Larbi, Belkacem Soundes
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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered as a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.
Keywords: Text detection, CNN, PZM, deep learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401102 Effect of a Linear-Exponential Penalty Functionon the GA-s Efficiency in Optimization of a Laminated Composite Panel
Authors: A. Abedian, M. H. Ghiasi, B. Dehghan-Manshadi
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A stiffened laminated composite panel (1 m length × 0.5m width) was optimized for minimum weight and deflection under several constraints using genetic algorithm. Here, a significant study on the performance of a penalty function with two kinds of static and dynamic penalty factors was conducted. The results have shown that linear dynamic penalty factors are more effective than the static ones. Also, a specially combined linear-exponential function has shown to perform more effective than the previously mentioned penalty functions. This was then resulted in the less sensitivity of the GA to the amount of penalty factor.Keywords: Genetic algorithms, penalty function, stiffenedcomposite panel, finite element method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16651101 Design and Implementation of an Image Based System to Enhance the Security of ATM
Authors: Seyed Nima Tayarani Bathaie
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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.
Keywords: Face detection algorithm, Haar features, Security of ATM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20981100 Selection of Relevant Servers in Distributed Information Retrieval System
Authors: Benhamouda Sara, Guezouli Larbi
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Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.
Keywords: Distributed information retrieval, relevance, server selection, collection selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13671099 Intelligent Aid-Analysis Based on the Use of Digital Twin: Application to Electronic Warfare System
Authors: L. Chaussy, M. Nouvel
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Workload of the system engineers during Integration Validation Verification process of Electronic Warfare Systems (EWS) is growing with complexity of the systems and with the diversity of tested cases (diversity of operational scenario in front of EWS). Even if the use of Digital Twin makes easier conception and development phases in term of planning and test equipment availability, time to analyze tests results is still too long and too complex. The idea to reduce the system engineer’s workload and improve test coverage is to introduce some intelligent and aid-analysis algorithms to improve this step.
Keywords: Analysis tools, automatic testing, digital twin, electronic warfare system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3631098 A Simulation Software for DNA Computing Algorithms Implementation
Authors: M. S. Muhammad, S. M. W. Masra, K. Kipli, N. Zamhari
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The capturing of gel electrophoresis image represents the output of a DNA computing algorithm. Before this image is being captured, DNA computing involves parallel overlap assembly (POA) and polymerase chain reaction (PCR) that is the main of this computing algorithm. However, the design of the DNA oligonucleotides to represent a problem is quite complicated and is prone to errors. In order to reduce these errors during the design stage before the actual in-vitro experiment is carried out; a simulation software capable of simulating the POA and PCR processes is developed. This simulation software capability is unlimited where problem of any size and complexity can be simulated, thus saving cost due to possible errors during the design process. Information regarding the DNA sequence during the computing process as well as the computing output can be extracted at the same time using the simulation software.Keywords: DNA computing, PCR, POA, simulation software
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18001097 Practical Aspects of Face Recognition
Authors: S. Vural, H. Yamauchi
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Current systems for face recognition techniques often use either SVM or Adaboost techniques for face detection part and use PCA for face recognition part. In this paper, we offer a novel method for not only a powerful face detection system based on Six-segment-filters (SSR) and Adaboost learning algorithms but also for a face recognition system. A new exclusive face detection algorithm has been developed and connected with the recognition algorithm. As a result of it, we obtained an overall high-system performance compared with current systems. The proposed algorithm was tested on CMU, FERET, UNIBE, MIT face databases and significant performance has obtained.Keywords: Adaboost, Face Detection, Face recognition, SVM, Gabor filters, PCA-ICA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15901096 Advanced Image Analysis Tools Development for the Early Stage Bronchial Cancer Detection
Authors: P. Bountris, E. Farantatos, N. Apostolou
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Autofluorescence (AF) bronchoscopy is an established method to detect dysplasia and carcinoma in situ (CIS). For this reason the “Sotiria" Hospital uses the Karl Storz D-light system. However, in early tumor stages the visualization is not that obvious. With the help of a PC, we analyzed the color images we captured by developing certain tools in Matlab®. We used statistical methods based on texture analysis, signal processing methods based on Gabor models and conversion algorithms between devicedependent color spaces. Our belief is that we reduced the error made by the naked eye. The tools we implemented improve the quality of patients' life.Keywords: Bronchoscopy, digital image processing, lung cancer, texture analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14261095 Mining News Sites to Create Special Domain News Collections
Authors: David B. Bracewell, Fuji Ren, Shingo Kuroiwa
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We present a method to create special domain collections from news sites. The method only requires a single sample article as a seed. No prior corpus statistics are needed and the method is applicable to multiple languages. We examine various similarity measures and the creation of document collections for English and Japanese. The main contributions are as follows. First, the algorithm can build special domain collections from as little as one sample document. Second, unlike other algorithms it does not require a second “general" corpus to compute statistics. Third, in our testing the algorithm outperformed others in creating collections made up of highly relevant articles.Keywords: Information Retrieval, News, Special DomainCollections,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14701094 Exploring Counting Methods for the Vertices of Certain Polyhedra with Uncertainties
Authors: Sammani Danwawu Abdullahi
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Vertex Enumeration Algorithms explore the methods and procedures of generating the vertices of general polyhedra formed by system of equations or inequalities. These problems of enumerating the extreme points (vertices) of general polyhedra are shown to be NP-Hard. This lead to exploring how to count the vertices of general polyhedra without listing them. This is also shown to be #P-Complete. Some fully polynomial randomized approximation schemes (fpras) of counting the vertices of some special classes of polyhedra associated with Down-Sets, Independent Sets, 2-Knapsack problems and 2 x n transportation problems are presented together with some discovered open problems.Keywords: Approximation, counting with uncertainties, mathematical programming, optimization, vertex enumeration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1348