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Optimal Experiments With Seismic Sensors

Optimal Experiments With Seismic Sensors

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： M. Alam V. Cevher J.H. McClellan Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

In this paper, we consider the problem of detecting and locating buried land mines and subsurface objects by using seismic waves. We demonstrate an adaptive seismic system that maneuvers an array of receivers, according to an optimal positioning algorithm based on the theory of optimal experiments, to minimize the number of distinct measurements to localize the mine. The adaptive localization algorithm is tested using numerical model data as well as laboratory measurements performed in a facility at Georgia Tech. It is envisioned that the future systems should be able to incorporate this new method into portable mobile mine-location systems

关键词： Landmine detection Seismic measurements Buried object detection Seismic waves Adaptive systems Adaptive arrays Position measurement Testing Numerical models Laboratories

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Noise Robust Aurora-2 Speech Recognition Employing a Codebook-Constrained Kalman Filter Preprocessor

Noise Robust Aurora-2 Speech Recognition Employing a Codeboo...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： V. Krishnan S.M. Siniscalchi D.V. Anderson M.A. Clements Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

In this paper, a speech signal estimation framework involving Kalman filters for use as a front-end to the Aurora-2 speech recognition task is presented. Kalman-filter based speech estimation algorithms assume autoregressive (AR) models for the speech and the noise signals. In this paper, the parameters of the AR models are estimated using a expectation-maximization approach. The key to the success of the proposed algorithm is the constraint on the AR model parameters corresponding to the speech signal to belong to a codebook trained on AR parameters obtained from clean speech signals. Aurora-2 noise-robust speech recognition experiments are performed to demonstrate the success of the codebook-constrained Kalman filter in improving speech recognition accuracy in noisy environments. Results with both clean and multi-conditional training are provided to show the improvements in the recognition accuracy compared to the base-line system where no pre-processing is employed

关键词： Noise robustness Speech recognition Speech enhancement Speech processing Automatic speech recognition signal processing State estimation Working environment noise Feature extraction Time measurement

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Imaging and Detector Framework for Seismic Landmine Detection

Imaging and Detector Framework for Seismic Landmine Detectio...

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Sensor Array and Multichannel signal processing Workshop

作者： M. Alam J.H. McClellan Center for Signal and Image Processing Georgia Institute of Technology School of Electrical and Computer Engineering Atlanta GA USA

In this paper, we consider the problem of detecting and locating buried landmines and subsurface objects by using seismic waves measured with sources and receivers on the surface. An imaging algorithm is proposed which uses the separated forward and reflected waves obtained via a Prony-based spectrum analysis technique. The imaging algorithm is followed by an energy detector. The resulting algorithms will are verified by using the experimental data containing mines and clutter

关键词： Landmine detection Detectors Sensor arrays Seismic waves Surface waves Data mining Resonance Laboratories Testing image reconstruction

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High SNR flexible top hat monopole probe for 1.5 T MRI

High SNR flexible top hat monopole probe for 1.5 T MRI

引用

作者： Mohammadzadeh, M. Shahabadi, M. Soltanian-Zadeh, H. Tavakoli, A. Rafiei, B. Javidnia, D. Oghabian, M.A. Department of Physics Amir-Kabir University of Technology Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Electrical Engineering Amir-Kabir University of Technology Tehran Iran Medical Imaging Center Imam Khomeyni Hospital Tehran Iran Research Center for Science and Technology in Medicine Tehran University of Medical Sciences Tehran Iran

In this paper, design principles and application of a thin and flexible intravascular top hat monopole probe with increased signal-to-noise ratio (SNR) and improved longitudinal and radial coverage are described and compared with the conventional monopole probe. The top hat probe is constructed by removing a segment of the shield of a coaxial cable. A flexible thin copper foil in contact with the inner conductor of the cable is added to the end section of the cable. The copper foil acts as an antenna top hat load increasing the uniformity of the current distribution on the probe and establishes a uniform region of SNR distribution around the probe. Improvement of the SNR distribution of the top hat probe relative to the conventional monopole probe is evaluated using quantitative indices. Experimental results show that for the top hat probe, the ratio of the maximum image SNR to its relative standard deviation (SR) is 2.73 times higher than that of a conventional probe. © 2006 IOP Publishing Ltd.

关键词： Medical imaging

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Multi-modal human verification using face and speech

Multi-modal human verification using face and speech

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Fourth IEEE International Conference on computer Vision Systems, ICVS'06

作者： Park, Changhan Choi, Taewoong Kim, Youngouk Kim, Soonhyob Namkung, Jaechan Paik, Joonki Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-dong Tongjak-Ku Seoul 156-756 Korea Republic of Multimedia Signal Processing Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Precision Machinery Center Korea Electronics Technology Institute 401-402 B/D 193 Yakdae-dong Wonmi-Gu Puchon Kyunggido 420-140 Korea Republic of

ISBN: (纸本)0769525067

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time. © 2006 IEEE.

关键词： Face recognition

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Multi-Modal Human Verification Using Face and Speech

Multi-Modal Human Verification Using Face and Speech

引用

IEEE International Conference on computer Vision Systems (ICVS)

作者： Changhan Park Joonki Paik Taewoong Choi Soonhyob Kim Youngouk Kim J. Namkung Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Multimedia Signal Processing Laboratory Kwangwoon University Seoul South Korea Precision Machinery Center Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University Seoul South Korea

关键词： Humans Speech Face detection Face recognition Biometrics Principal component analysis Feature extraction Hidden Markov models image edge detection Laboratories

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3D ROC Analysis for Medical Imaging Diagnosis

3D ROC Analysis for Medical Imaging Diagnosis

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Su Wang C.-I. Chang Sheng-Chih Yang Giu-Cheng Hsu Hsian-He Hsu Pau-Choo Chung Shu-Mei Guo San-Kan Lee Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA Department of Electrical Engineering National Cheng Kung University Taiwan Department of Radiology Tri-Service General Hospital and National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Taiwan Administrative Office Suao Veterans Hospital Yilan Taiwan

Receiver operating characteristics (ROC) has been widely used as a performance evaluation tool to measure effectiveness of medical modalities. It is derived from a standard detection theory with false alarm and detection power interpreted as false positive (FP) and true positive (TP) respectively in terms of medical diagnosis. The ROC curve is plotted based on TP versus FP via hard decisions. This paper presents a three dimensional (3D) ROC analysis which extends the traditional two-dimensional (2D) ROC analysis by including a threshold parameter in a third dimension resulting from soft decisions, (SD). As a result, a 3D ROC curve can be plotted based on three parameters, TP, FP and SD. By virtue of such a 3D ROC curve three two-dimensional (2D) ROC curves can be derived, one of which is the traditional 2D ROC curve of TP versus FP with SD reduced to hard decision. In order to illustrate its utility in medical diagnosis, its application to magnetic resonance (MR) image classification is demonstrated

关键词： image analysis Biomedical imaging Radar detection Medical diagnosis Detectors computer science Hospitals Medical diagnostic imaging Magnetic analysis Performance analysis

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AUTOMATED SEGMENTATION OF THE ARTICULAR SPACE IN MR imageS OF THE HIP JOINT

AUTOMATED SEGMENTATION OF THE ARTICULAR SPACE IN MR IMAGES O...

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2006 IET International Conference on Visual Information engineering

作者： M. Khanmohammadi R. A. Zoroofi Y. Sato T. Nishii K. Nakanishi H. Tanaka N. Sugano H. Yoshikawa H. Nakamura S. Tamura Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran Divsion of Image Analysis Osaka University Graduate School of Medicine Osaka Japan Department of Orthopaedic Surgery Osaka University Graduate School of Medicine Osaka Japan Department of Radiology Osaka University Graduate School of Medicine Osaka Japan

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Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy

Medical Data Mining using Particle Swarm Optimization for Te...

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Congress on Evolutionary Computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Hardware-efficient distributed arithmetic architecture for high-order digital filters

Hardware-efficient distributed arithmetic architecture for h...

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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05

作者： Yoo, Heejong Anderson, David V. Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332 United States

ISBN: (纸本)0780388747

This paper presents a new memory-efficient distributed arithmetic (DA) architecture for high-order FIR filters. The proposed architecture is based on a memory reduction technique for DA look-up-tables (LUTs);it requires fewer transistors for high-order filters than original LUT-based DA, DA-offset binary coding (DA-OBC), and the LUT-less DA-OBC. Recursive iteration of the memory reduction technique significantly increases the maximum number of filter order implementable on an FPGA platform by not only saving transistor counts, but also balancing hardware usage between logic element (LE) and memory. FPGA implementation results confirm that the proposed DA architecture can implement a 1024-tap FIR filter with significantly smaller area usage (< 50%) than the original LUT-based DA and the LUT-less DA-OBC. © 2005 IEEE.

关键词： Distributed computer systems

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