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Articles 61 - 84 of 84
Full-Text Articles in Engineering
2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)
2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)
Electrical & Computer Engineering Faculty Publications
Pose and illumination are identified as major problems in 2D face recognition (FR). It has been theoretically proven that the more diversified instances in the training phase, the more accurate and adaptable the FR system appears to be. Based on this common awareness, researchers have developed a large number of photographic face databases to meet the demand for data training purposes. In this paper, we propose a novel scheme for 2D face database diversification based on 3D face modeling and computer graphics techniques, which supplies augmented variances of pose and illumination. Based on the existing samples from identical individuals of …
Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)
Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)
Electrical & Computer Engineering Faculty Publications
At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, …
Special Issue On Information Dissemination And New Services In P2p Systems, Min Song, Sachin Shetty, Wenbin Jiang, E. K. Park
Special Issue On Information Dissemination And New Services In P2p Systems, Min Song, Sachin Shetty, Wenbin Jiang, E. K. Park
Electrical & Computer Engineering Faculty Publications
Information dissemination is an important P2P application that has received considerable research attention in recent years. P2P information dissemination systems range from simple file sharing applications to more complex systems that allows users to securely and efficiently publish, organize, index, search, update and retrieve data in a distributed storage medium. For complex P2P information dissemination systems, there is a need for features which include security, anonymity, fairness, scalability, resource management, and organization capabilities. For effective information dissemination, following features of P2P systems and infrastructure need to be updated: distributed object location and routing mechanisms, novel approaches to content replication, caching …
Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)
Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)
Electrical & Computer Engineering Faculty Publications
This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classis and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random under-sampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving test dataset show that accuracies for minority classes …
Eeg Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen, John Musson, Jiang Li, Frederick Mckenzie, Guangfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)
Eeg Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen, John Musson, Jiang Li, Frederick Mckenzie, Guangfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)
Electrical & Computer Engineering Faculty Publications
In this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We compared the WNN algorithm with the ICA technique and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.
Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie
Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie
Electrical & Computer Engineering Faculty Publications
In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% …
Automatic Detection Of Aircraft Emergency Landing Sites, Yu-Fei Shen, Zia-Ur Rahman, Dean Krusienski, Jiang Li, Zia-Ur Rahman (Ed.), Stephen E. Reichenbach (Ed.), Mark Allen Neifeld (Ed.)
Automatic Detection Of Aircraft Emergency Landing Sites, Yu-Fei Shen, Zia-Ur Rahman, Dean Krusienski, Jiang Li, Zia-Ur Rahman (Ed.), Stephen E. Reichenbach (Ed.), Mark Allen Neifeld (Ed.)
Electrical & Computer Engineering Faculty Publications
An automatic landing site detection algorithm is proposed for aircraft emergency landing. Emergency landing is an unplanned event in response to emergency situations. If, as is unfortunately usually the case, there is no airstrip or airfield that can be reached by the un-powered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on the external environmental factors that can impair …
Marine Buoy Detection Using Circular Hough Transform, Loc Tran, Justin Selfridge, Gene Hou, Jiang Li
Marine Buoy Detection Using Circular Hough Transform, Loc Tran, Justin Selfridge, Gene Hou, Jiang Li
Electrical & Computer Engineering Faculty Publications
A low cost method for buoy detection in maritime settings is presented using inexpensive digital cameras. In this method, the circular Hough transform is applied to an edge image to circular objects in the image. The center of these circles will signify the locations of each buoy. The known color information of the buoys is also used to enhance the performance by removing false detections. The algorithm is compared to an approach that locates buoys purely on color information. In order to validate the method, we test the approach synthetically and also with real images captured from a small surface …
3d Face Reconstruction From Limited Images Based On Differential Evolution, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Andrew G. Tescher (Ed.)
3d Face Reconstruction From Limited Images Based On Differential Evolution, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Andrew G. Tescher (Ed.)
Electrical & Computer Engineering Faculty Publications
3D face modeling has been one of the greatest challenges for researchers in computer graphics for many years. Various methods have been used to model the shape and texture of faces under varying illumination and pose conditions from a single given image. In this paper, we propose a novel method for the 3D face synthesis and reconstruction by using a simple and efficient global optimizer. A 3D-2D matching algorithm which employs the integration of the 3D morphable model (3DMM) and the differential evolution (DE) algorithm is addressed. In 3DMM, the estimation process of fitting shape and texture information into 2D …
Enhancement Technique For Aerial Images, Sertan Erkanli, Ahmet Gungor Pakfiliz, Jiang Li
Enhancement Technique For Aerial Images, Sertan Erkanli, Ahmet Gungor Pakfiliz, Jiang Li
Electrical & Computer Engineering Faculty Publications
Recently, we proposed an enhancement technique for uniformly and non-uniformly illuminated dark images that provides high color accuracy and better balance between the luminance and the contrast in images to improve the visual representations of digital images. In this paper we define an improved version of the proposed algorithm to enhance aerial images in order to reduce the gap between direct observation of a scene and its recorded image.
Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)
Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)
Electrical & Computer Engineering Faculty Publications
In a recent study [1], we investigated the feasibility of predicting brain tumor progression based on multiple MRI series and we tested our methods on seven patients' MRI images scanned at three consecutive visits A, B and C. Experimental results showed that it is feasible to predict tumor progression from visit A to visit C using a model trained by the information from visit A to visit B. However, the trained model failed when we tried to predict tumor progression from visit B to visit C, though it is clinically more important. Upon a closer look at the MRI scans …
Security In Ad Hoc Networks And Pervasive Computing, Isaac Z. Wu, X.-Y. Li, M. Song, C.-M. Liu
Security In Ad Hoc Networks And Pervasive Computing, Isaac Z. Wu, X.-Y. Li, M. Song, C.-M. Liu
Electrical & Computer Engineering Faculty Publications
Pervasive computing is an exciting and blooming research field, in which innovative techniques and applications are continuously emerging and aim to provide ambient and personalized services to users with high quality. Ad hoc networks are wireless, self-organizing systems formed by cooperating nodes within communication range of each other that form temporary networks. Their topology is dynamic, decentralized, ever changing and the nodes may move around arbitrarily. The last few years have witnessed a wealth of research ideas on ad hoc networking that are moving rapidly into implemented standards. Technology under development for ad hoc networks and pervasive computing is making …
Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Electrical & Computer Engineering Faculty Publications
A machine learning technique is presented for assessing brain tumor progression by exploring six patients' complete MRI records scanned during their visits in the past two years. There are ten MRI series, including diffusion tensor image (DTI), for each visit. After registering all series to the corresponding DTI scan at the first visit, annotated normal and tumor regions were overlaid. Intensity value of each pixel inside the annotated regions were then extracted across all of the ten MRI series to compose a 10 dimensional vector. Each feature vector falls into one of three categories:normal, tumor, and normal but progressed to …
Seasonal Adaptation Of Vegetation Color In Satellite Images For Flight Simulations, Yuzhong Shen, Jiang Li, Vamsi Mantena, Srinivas Jakkula
Seasonal Adaptation Of Vegetation Color In Satellite Images For Flight Simulations, Yuzhong Shen, Jiang Li, Vamsi Mantena, Srinivas Jakkula
Electrical & Computer Engineering Faculty Publications
Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper proposes a novel method that identifies vegetative areas in satellite images and then alters vegetation color to simulate seasonal changes based on training image pairs. The proposed method first generates a vegetation map for pixels corresponding to vegetative areas, using ISODATA clustering and vegetation classification. The ISODATA algorithm determines the number of clusters automatically. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. Six features are then computed …
Dynamic Adaptation Of Joint Transmission Power And Contention Window In Vanet, Danda B. Rawat, Gongjun Yan, Dimitrie C. Popescu, Michele C. Weigle, Stephan Olariu
Dynamic Adaptation Of Joint Transmission Power And Contention Window In Vanet, Danda B. Rawat, Gongjun Yan, Dimitrie C. Popescu, Michele C. Weigle, Stephan Olariu
Electrical & Computer Engineering Faculty Publications
In this paper, we propose an algorithm for joint adaptation of transmission power and contention window to improve the performance of vehicular network in a cross layer approach. The high mobility of vehicles in vehicular communication results in the change in topology of the Vehicular Ad-hoc Network (VANET) dynamically, and the communication link between two vehicles might remain active only for short duration of time. In order for VANET to make a connection for long time and to mitigate adverse effects due to high and fixed transmission power, the proposed algorithm adapts transmission power dynamically based on estimated local traffic …
Parameter Optimization For Image Denoising Based On Block Matching And 3d Collaborative Filtering, Ramu Pedada, Emin Kugu, Jiang Li, Zhanfeng Yue, Yuzhong Shen, Josien P.W. Pluim (Ed.), Benoit M. Dawant (Ed.)
Parameter Optimization For Image Denoising Based On Block Matching And 3d Collaborative Filtering, Ramu Pedada, Emin Kugu, Jiang Li, Zhanfeng Yue, Yuzhong Shen, Josien P.W. Pluim (Ed.), Benoit M. Dawant (Ed.)
Electrical & Computer Engineering Faculty Publications
Clinical MRI images are generally corrupted by random noise during acquisition with blurred subtle structure features. Many denoising methods have been proposed to remove noise from corrupted images at the expense of distorted structure features. Therefore, there is always compromise between removing noise and preserving structure information for denoising methods. For a specific denoising method, it is crucial to tune it so that the best tradeoff can be obtained. In this paper, we define several cost functions to assess the quality of noise removal and that of structure information preserved in the denoised image. Strength Pareto Evolutionary Algorithm 2 (SPEA2) …
Towards A Metric For The Assessment Of Safety Critical Control Systems, Oscar R. Gonzalez, Jorge R. Chavez-Fuentes, W. Steven Gray
Towards A Metric For The Assessment Of Safety Critical Control Systems, Oscar R. Gonzalez, Jorge R. Chavez-Fuentes, W. Steven Gray
Electrical & Computer Engineering Faculty Publications
There is a need for better integration of the fault tolerant and the control designs for safety critical systems such as aircraft. The dependability of current designs is assessed primarily with measures of the interconnection of fault tolerant components: the reliability function and the mean time to failure. These measures do not directly take into account the interaction of the fault tolerant components with the dynamics of the aircraft. In this paper, a first step to better integrate these designs is made. It is based on the observation that unstable systems are intrinsically unreliable and that a necessary condition for …
Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Electrical & Computer Engineering Faculty Publications
Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …
Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
Electrical & Computer Engineering Faculty Publications
We evaluate and improve an existing curvature-based region growing algorithm for colonic polyp detection for our CT colonography (CTC) computer-aided detection (CAD) system by using Pareto fronts. The performance of a polyp detection algorithm involves two conflicting objectives, minimizing both false negative (FN) and false positive (FP) detection rates. This problem does not produce a single optimal solution but a set of solutions known as a Pareto front. Any solution in a Pareto front can only outperform other solutions in one of the two competing objectives. Using evolutionary algorithms to find the Pareto fronts for multi-objective optimization problems has been …
Validating Pareto Optimal Operation Parameters Of Polyp Detection Algorithms For Ct Colonography, Jiang Li, Adam Huang, Nicholas Petrick, Jianhua Yao, Ronald M. Summers, Maryellen L. Giger (Ed.), Nico Karssemeijer (Ed.)
Validating Pareto Optimal Operation Parameters Of Polyp Detection Algorithms For Ct Colonography, Jiang Li, Adam Huang, Nicholas Petrick, Jianhua Yao, Ronald M. Summers, Maryellen L. Giger (Ed.), Nico Karssemeijer (Ed.)
Electrical & Computer Engineering Faculty Publications
We evaluated a Pareto front-based multi-objective evolutionary algorithm for optimizing our CT colonography (CTC) computer-aided detection (CAD) system. The system identifies colonic polyps based on curvature and volumetric based features, where a set of thresholds for these features was optimized by the evolutionary algorithm. We utilized a two-fold cross-validation (CV) method to test if the optimized thresholds can be generalized to new data sets. We performed the CV method on 133 patients; each patient had a prone and a supine scan. There were 103 colonoscopically confirmed polyps resulting in 188 positive detections in CTC reading from either the prone or …
The Formal Laplace-Borel Transform Of Fliess Operators And The Composition Product, Yaqin Li, W. Steven Gray
The Formal Laplace-Borel Transform Of Fliess Operators And The Composition Product, Yaqin Li, W. Steven Gray
Electrical & Computer Engineering Faculty Publications
The formal Laplace-Borel transform of an analytic integral operator, known as a Fliess operator, is defined and developed. Then, in conjunction with the composition product over formal power series, the formal Laplace-Borel transform is shown to provide an isomorphism between the semigroup of all Fliess operators under operator composition and the semigroup of all locally convergent formal power series under the composition product. Finally, the formal Laplace-Borel transform is applied in a systems theory setting to explicitly derive the relationship between the formal Laplace transform of the input and output functions of a Fliess operator. This gives a compact interpretation …
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Electrical & Computer Engineering Faculty Publications
We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …
Performance Analysis And Validation Of A Recoverable Flight Control System In A Simulated Neutron Environment, Hong Zhang, W. Steven Gray, Oscar R. Gonzalez
Performance Analysis And Validation Of A Recoverable Flight Control System In A Simulated Neutron Environment, Hong Zhang, W. Steven Gray, Oscar R. Gonzalez
Electrical & Computer Engineering Faculty Publications
This paper introduces a class of stochastic hybrid models for the analysis of closed-loop control systems implemented with NASA's Recoverable Computer System. Such Recoverable Computer Systems have been proposed to insure reliable control performance in harsh environments. The stochastic hybrid models consist of either a stochastic finite-state automaton or a finite-state machine driven by a Markov input, which in turn drives a switched linear discrete-time dynamical system. Their stability and output tracking performance are analyzed using an extension of the existing theory for Markov jump-linear systems. For illustration, a stochastic hybrid model is used to calculate the tracking error performance …
Design And Implementation Of Fuzzy Logic Controllers. Thesis Final Report, 27 July 1992 - 1 January 1993, Osama A. Abihana, Oscar R. Gonzalez
Design And Implementation Of Fuzzy Logic Controllers. Thesis Final Report, 27 July 1992 - 1 January 1993, Osama A. Abihana, Oscar R. Gonzalez
Electrical & Computer Engineering Faculty Publications
The main objectives of our research are to present a self-contained overview of fuzzy sets and fuzzy logic, develop a methodology for control system design using fuzzy logic controllers, and to design and implement a fuzzy logic controller for a real system. We first present the fundamental concepts of fuzzy sets and fuzzy logic. Fuzzy sets and basic fuzzy operations are defined. In addition, for control systems, it is important to understand the concepts of linguistic values, term sets, fuzzy rule base, inference methods, and defuzzification methods. Second, we introduce a four-step fuzzy logic control system design procedure. The design …