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Improved particle swarm optimization and applications to Hidden Markov Model and Ackley function

Improved particle swarm optimization and applications to Hid...

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IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA)

作者： Saeed Motiian Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA

Particle Swarm Optimization (PSO) is an algorithm based on social intelligence, utilized in many fields of optimization. In applications like speech recognition, due to existence of high dimensional matrices, the speed of standard PSO is very low. In addition, PSO may be trapped in a local optimum. In this paper, we introduce a novel algorithm that is faster and generates superior results than the standard PSO. Also, the probability of being trapped in a local optimum is decreased. To illustrate advantages of the proposed algorithm, we use it to train a Hidden Markov Model (HMM) and find the minimum of the Ackley function.

关键词： Hidden Markov models Training Particle swarm optimization Speech processing Educational institutions Algorithm design and analysis Optimization

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Evaluation of functional connectivity in control and ADHD subjects by generalized Canonical Correlation and Probabilistic Independent Component analysis

Evaluation of functional connectivity in control and ADHD su...

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Iranian Conference of Biomedical engineering (ICBME)

作者： AmirEhsan Lashkari Hamid Soltanian-Zadeh GholamAli Hosseinzadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA

Functional connectivity can be evaluated by temporal correlation between spatial neurophysiologic events or correlation between neural activities of brain regions. Unlike anatomical connectivity which represents physical connections between two brain regions, functional connectivity investigates interactions between brain regions. In this study, we implemented and evaluated Probabilistic Independent Component analysis (PICA) and generalized Canonical Correlation analysis (gCCA) on resting state data of healthy subjects and subjects with ADHD disorders from NITRC database. This was done to detect brain functional connectivity and compare the results in normal and diseased subjects. In addition, speed of the methods was compared. Our study shows that relative to PICA, gCCA has higher precision and accuracy and lower computational complexity and run time in addition to capability of extracting more reproducible statistical maps in both control and ADHD subjects.

关键词： Correlation Magnetic resonance imaging Independent component analysis Educational institutions Biomedical engineering Probabilistic logic Basal ganglia

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Effect of Different Diffusion Maps on Registration Results

Effect of Different Diffusion Maps on Registration Results

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Iranian Machine vision and image Processing (MVIP)

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory (BiSIPL) Sharif University of Technology Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper, we compare registration results obtained using different diffusion maps extracted from diffusion tensor imaging (DTI). Fractional Anisotropy (FA) and Ellipsoidal Area Ratio (EAR) are two diffusion maps (indices) that may be used for image registration. First, we use FA maps to find deformation matrix and register diffusion weighted images. Then, we use EAR maps and finally we use both of FA and EAR maps to register diffusion weighted images. The difference between FA values before deformation and after registration using the FA alone or EAR alone has a median of 0.57 and using both of them has a median of 0.29. Therefore, the results of registration using both of the FA and EAR indices are superior to those obtained using only one of them alone.

关键词： Ear Diffusion tensor imaging Tensile stress Registers Eigenvalues and eigenfunctions Anisotropic magnetoresistance image registration

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Combining global and local features for food identification in dietary assessment

Combining global and local features for food identification ...

引用

IEEE International Conference on image Processing

作者： Marc Bosch Fengqing Zhu Nitin Khanna Carol J. Boushey Edward J. Delp School of Electrical and Computer Engineering Video and Image Processing Laboratory USA Department of Foods and Nutrition Purdue University West Lafayette IN USA

Many chronic diseases, such as heart diseases, diabetes, and obesity, can be related to diet. Hence, the need to accurately measure diet becomes imperative. We are developing methods to use image analysis tools for the identification and quantification of food consumed at a meal. In this paper we describe a new approach to food identification using several features based on local and global measures and a “voting” based late decision fusion classifier to identify the food items. Experimental results on a wide variety of food items are presented.

关键词： image color analysis Visualization Feature extraction image segmentation Color Conferences Vectors

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Sport Video Classification Using an Ensemble Classifier

Sport Video Classification Using an Ensemble Classifier

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Iranian Machine vision and image Processing (MVIP)

作者： Mohamad Hoseyn Sigari Samaneh Abbasi Sureshjani Hamid Soltanian-Zadeh Control & Intelligent Processing Center of Excellence (CIPCE) School of Electrical & Computer Engineering College of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA

Sport video classification is an application of video analysis which can be useful in video indexing and retrieval. In this article, a new method for sport video classification using ensemble classifier is proposed. The proposed method uses 6 features: 3 dominant colors, dominant gray level, cut rate and motion rate. These features are classified by 4 simple classifiers in an ensemble classifier: Nearest Neighbor (NN), Linear Discriminant analysis (LDA), Decision Tree (DT) and Probabilistic Neural Network (PNN). To combine the output of simple classifiers and make final decision, weighted majority vote is used while the weight of each simple classifier is equal to corresponding correct classification rate (CCR). Experimental result shows that the CCR of proposed system is 78.8%. In this experiment, 104 clips in 7 different sport classes are used: football, basketball, tennis, swimming, futsal, ski and box.

关键词： Feature extraction Color image color analysis Classification algorithms Accuracy Artificial neural networks Histograms

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Traffic speed measurement using spatio-temporal model and frequency domain analysis

Traffic speed measurement using spatio-temporal model and fr...

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International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology

作者： Rungchokanun, Arucha Areekul, Vutipong Siddhichai, Supakorn Kunieda, Hiroaki Department of Electrical Engineering Kasetsart University 10900 Thailand Image Technology Laboratory National Electronics and Computer Technology Center Pathumthani 12120 Thailand Department of Communication and Integrated Systems Tokyo Institute of Technology S3-65 2-12-1 Ookayama Meguro-ku Tokyo 152-8550 Japan

ISBN: (纸本)9781457704246

In traffic monitoring applications, traffic speed is an important parameter of traffic management. The method for traffic speed measurement using video based on Spatio-Temporal (ST) model and frequency domain analysis is proposed in this paper. This method is designed to be able to measure the traffic speed in every pattern of road. The novel of proposed method is unfolding the edge information on ST model and analyse them in frequency domain to determine traffic speed. The proposed method is evaluated by compare with actual speed. The traffic speed is measured accurately 97.1%. © 2011 IEEE.

关键词： Frequency domain analysis

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Universal Steganalysis Based on Local Prediction Error in Wavelet Domain

Universal Steganalysis Based on Local Prediction Error in Wa...

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Anahita Shojaei-Hashemi Mostafa Mehdipour-Ghazi Shahrokh Ghaemmaghami Hamid Soltanian-Zadeh School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electronics Research Institute Sharif University of Technology Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes.

关键词： Equations Mathematical model Payloads Transform coding Correlation Educational institutions Reliability

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Comparison of classifier performance for information fusion in automated Diabetic Retinopathy screening

Comparison of classifier performance for information fusion ...

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IEEE International Symposium on Biomedical Imaging

作者： Meindert Niemeijer Michael D. Abràmoff Niranjan Joshi Michael Brady Department of Ophthalmology and Visual Sciences Department of Electrical and Computer Engineering University of Iowa Iowa IA USA Wolfson Medical Vision Laboratory University of Oxford Oxford UK

Diabetic Retinopathy (DR) is a vascular disorder affecting the retina due to prolonged Diabetes. It can lead to sudden vision loss in advanced stages. Screening and routine monitoring is the most effective way of avoiding vision loss due to DR. Abramoff et al. developed and evaluated an automated DR screening system. One of the most important parts of this system, the information fusion module, combines information obtained from different images and various image properties. Niemeijer et al. compared several methods for DR information fusion and concluded that k-Nearest Neighbour (kNN) provided the best performance for their system. The aim of this work was to compare performance of the Random Forest (RF) classifier with that of the kNN classifier for DR information fusion. We performed experiments on a dataset containing images from 10303 eye examinations. Additionally we also compared performance of the two classifiers in an important sub-problem of DR screening - red lesion detection. In both the experiments, the RF classifier showed significantly better performance.

关键词： Radio frequency Diabetes Lesions Training Retinopathy Vegetation Sensitivity

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VHR image segmentation using over segmented regions in a MRF model

VHR image segmentation using over segmented regions in a MRF...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Örsan Aytekin Yousef Rezaeitabar İlkay Ulusoy Computer Vision and Intelligent Systems Research Laboratory Department of Electrical and Electronics Engineering METU Ankara Turkey Orta Dogu Teknik Universitesi Ankara Ankara TR

This paper presents a segmentation method that exploits object based region merging to delineate the context of the image under investigation. There are two main steps. Initially, primitive objects are obtained by morphological operations that generate spectrally homogenous primitives. We assume that primitives are components of semantic objects that are of interest. Next, these primitives therefore are modeled and merged based on expectation maximization. We presented the results of the experiments applied to QuickBird images of rural and urban areas taken from the city of Ankara, Turkey. Experimental results demonstrate the capabilities of these methods along with their limitations.

关键词： image segmentation Morphology Clustering algorithms Urban areas Remote sensing image reconstruction Cities and towns

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Integrated database system for mobile dietary assessment and analysis

Integrated database system for mobile dietary assessment and...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Marc Bosch TusaRebecca Schap Fengqing Zhu Nitin Khanna Carol J. Boushey Edward J. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Foods and Nutrition Purdue University West Lafayette IN USA

Of the 10 leading causes of death in the US, 6 are related to diet. Unfortunately, methods for real-time assessment and proactive health management of diet do not currently exist. There are only minimally successful tools for historical analysis of diet and food consumption available. In this paper, we present an integrated database system that provides a unique perspective on how dietary assessment can be accomplished. We have designed three interconnected databases: an image database that contains data generated by food images, an experiments database that contains data related to nutritional studies and results from the image analysis, and finally an enhanced version of a nutritional database by including both nutritional and visual descriptions of each food. We believe that these databases provide tools to the healthcare community and can be used for data mining to extract diet patterns of individuals and/or entire social groups.

关键词： image analysis image databases Visualization Servers Visual databases

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