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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： L. Mihailescu W. Gast R. Lieder Forschungszentrum Juelich GmbH Julich Germany

For a practical implementation of Compton camera principles in /spl gamma/-ray imaging applications, large volume detectors are needed for a good efficiency, whereas for position sensitivity, a considerable number of segments per detector is required. Often, the overall number of segments and associated processing electronics make such a system prohibitive due to the involved cost, and other technical difficulties. In order to overcome this impediment, a new technical concept is introduced, which uses large volume high resolution semiconductor detectors (Ge) having implemented a low fold segmentation of their electrodes, and employing advanced signal processing methods to provide unprecedented position sensitivity. Involving only 1/160 of the number of segments otherwise required, using the WPC (wavelet transform + pattern recognition + correlation analysis) signal analysis method, the effective position sensitivity of the detectors is expected to reach mm per spatial coordinate. WPC is a new procedure which decomposes and extracts multiple interactions occurring in the detector by analyzing the features of the digitized detector segment signals. Although applied for Ge detectors, the concepts and methods presented could be easily transferred to Si(Li) and other room temperature semiconductor detectors of large volume.

关键词： Nuclear imaging image segmentation Gamma ray detection Gamma ray detectors signal analysis Cameras Optical imaging Costs Impedance signal resolution

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Whiteness-Based Bilevel Learning of Regularization Parameters in Imaging

Whiteness-Based Bilevel Learning of Regularization Parameter...

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European signal processing conference (EUSIPCO)

作者： Carlo Santambrogio Monica Pragliola Alessandro Lanza Marco Donatelli Luca Calatroni Science and High Technology Department University of Insubria Italy Laboratoire I3S CNRS UniCA Inria Sophia-Antipolis France Dept. of Mathematics and Applications University of Naples Federico II Italy Dept. of Mathematics University of Bologna Italy

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussian noise. Compared to supervised and weakly-supervised metrics relying either on the prior knowledge of reference data and/or on some (partial) knowledge on the noise statistics, the proposed approach optimizes the whiteness of the residual between the observed data and the observation model with no need of ground-truth data. We validate the approach on standard Total Variation-regularized image deconvolution problems which show that the proposed quality metric provides estimates close to the mean-square error oracle and to discrepancy-based principles.

关键词： Deconvolution AWGN Noise Imaging Europe Mean square error methods Noise measurement Standards Optimization image denoising

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Road Condition Detection and Crowdsourced Data Collection for Accident Prevention: A Deep Learning Approach

Road Condition Detection and Crowdsourced Data Collection fo...

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Workshops on image processing Theory, Tools and applications, IPTA

作者： Md Saroar Jahan Mominul Islam Md Sanjid Hossain Jhuma Kabir Mim Mourad Oussalah Nasrin Akter Centre for Machine Vision and Signal Processing (CMVS) Faculty of ITEE University of Oulu Oulu Finland Dept. of CSE Daffodil International University Dhaka Bangladesh Computer Vision and Pattern Recognition LUT Univerity Lappeenranta Finland CMVS Faculty of ITEE University of Oulu Oulu Finland

Bangladesh is one of the countries struggling to prevent road accidents, which is a global cause for concern. An early warning system that indicates road conditions can contribute to the prevention task. For this purpose, a deep-learning based approach using a Convolutional Neural Network (CNN) to learn from random road images the safety factor is developed. This results in a three-class categorization: (i) Severely risky roads, (ii) Mildly risky roads, and (iii) Normal roads. The application of deep learning techniques in this study yields an accuracy of 95.5% in detecting problematic road conditions. Furthermore, based on the study’s findings, a mobile application has been developed. The app enables real-time crowdsourced data collection of road conditions and provides a platform for users to share this information in real-time with other drivers, thereby, contributing to prevent accidents and raise awareness among drivers and users by pinpointing the location of the risky road. Finally, crowdsourced data has been reused to update the trained model, which further improves the classifier accuracy.

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An Effective Statistical Test Suite for Pseudorandom number Generators in Digital Signatures and Security Robustness Evaluation including a wavelet Test for Randomness

An Effective Statistical Test Suite for Pseudorandom number ...

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Symposium of image, signal processing, and Artificial Vision (STSIVA)

作者： Dimitrios A. Karras National & Kapodistrian University of Athens (NKUA) Greece

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

The need for random and pseudorandom numbers arises in many cryptographic applications including digital signatures management. For instance, common cryptosystems employ keys that must be generated in a random fashion. Many cryptographic protocols also require random or pseudorandom inputs at various points, e.g., for auxiliary quantities used in generating digital signatures, or for generating challenges in authentication protocols. A suitable set of statistical tests for randomness of message digests (MD5, SHA) and digital signatures DSA algorithms is outlined and evaluated in this paper based mainly on the revisions of National Institute of Standards and Technology (NIST) procedures in detecting deviations of a binary sequence from randomness. Although such an analysis exists for AES standard there is no similar study for message digests or digital signatures. The contribution of this paper lies in the attempt to fill in this gap from an educational point of view, providing relevant plots of the derived sequences, as well as to introduce a novel Discrete wavelet Transform Test for Randomness.

关键词： NIST Robustness Generators Cryptography Informatics Digital signatures Standards

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Multi-level Stress Assessment Using Multi-domain Fusion of ECG signal

Multi-level Stress Assessment Using Multi-domain Fusion of E...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Zeeshan Ahmad Naimul Mefraz Khan Department of Electrical and Computer Engineering Ryerson University Toronto ON Canada

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a burning research topic in biomedical signal processing. However, existing literature provides only binary assessment of stress, while multiple levels of assessment may be more beneficial for healthcare applications. Furthermore, in present research, ECG signal for stress analysis is examined independently in spatial domain or in transform domains but the advantage of fusing these domains has not been fully utilized. To get the maximum advantage of fusing different domains, we introduce a dataset with multiple stress levels and then classify these levels using a novel deep learning approach by converting ECG signal into signal images based on R-R peaks without any feature extraction. Moreover, We made signal images multimodal and multi-domain by converting them into time-frequency and frequency domain using Gabor wavelet transform (GWT) and Discrete Fourier Transform (DFT) respectively. Convolutional Neural networks (CNNs) are used to extract features from different modalities and then decision level fusion is performed for improving the classification accuracy. The experimental results on an in-house dataset collected with 15 users show that with proposed fusion framework and using ECG signal to image conversion, we reach an average accuracy of 85.45%.

关键词： Stress Electrocardiography Feature extraction Machine learning Discrete Fourier transforms Time-frequency analysis

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image compression and enlargement algorithms

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International Journal of Circuits, Systems and signal processing 2021年 15卷 836-846页

作者： Burova, I.G. Dem’yanovich, Yu.K. Terekhov, A.N. Altynova, A.Yu. Satanovskiy, A.D. Babushkin, A.A. St. Petersburg State University 7/9 Universitetskaya nab St.Petersburg199034 Russia

In some cases, there are problems associated with the compression and enlargement of images. The use of splines is quite effective in some cases. In this paper, a new image compression algorithm is presented. The features of increasing the size of an image when using local polynomial or non-polynomial splines are considered. The main method for enlarging an image is based on the use of splines of the second and third order of approximation. Polynomial and trigonometric splines are considered. To speed up the process of enlarging the image, we used the parallelization techniques. © 2021, North Atlantic University Union NAUN. All rights reserved.

关键词： image compression

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Tracking multiple maneuvering point targets using multiple filter bank in infrared image sequence

Tracking multiple maneuvering point targets using multiple f...

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

作者： M.A. Zaveri U.B. Desai S.N. Merchant SPANN Laboratory Electrical Engineering Department IIT Bombay India

Performance of any tracking algorithm depends upon the model selected to capture the target dynamics. In real world applications, no a priori knowledge about the target motion is available. Moreover, it could be a maneuvering target. The proposed method is able to track maneuvering or nonmaneuvering multiple point targets with large motion (/spl plusmn/20 pixels) using multiple filter bank in an IR image sequence in the presence of clutter and occlusion due to clouds. The use of multiple filters is not new, but the novel idea here is that it uses single-step decision logic to switch over between filters. Our approach does not use any a priori knowledge about maneuver parameters, nor does it exploit a parameterized nonlinear model for the target trajectories. This is in contrast to: (i) interacting multiple model (IMM) filtering which required the maneuver parameters, and (ii) extended Kalman filter (EKF) or unscented Kalman filter (UKF), both of which require a parameterized model for the trajectories. We compared our approach for target tracking with IMM filtering using EKF and UKF for nonlinear trajectory models. UKF uses the nonlinearity of the target model, where as a first order linearization is used in case of the EKF. RMS for the predicted position error (RMS-PPE) obtained using our proposed methodology is significantly less in case of highly maneuvering target.

关键词： Target tracking Filter bank Infrared imaging image sequences Switches Trajectory Filtering Pixel Clouds Logic

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Potentialities and limitations of hybrid space-airborne bistatic SAR

Potentialities and limitations of hybrid space-airborne bist...

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8th European conference on Synthetic Aperture Radar

作者： Antonio Moccia Alfredo Renga University of Naples “Federico II” Italy

Recently important experimentations were conducted on the use of space-airborne bistatic SAR. All the performed experiments relied on side-looking geometry both for the transmitter and the receiver, with platforms moving on parallel tracks, thus reducing geometric and radiometric distortions and focusing on synchronization and processing issues. However, present and future satellite illuminators shall allow more general observation geometries to be exploited for several additional applications with respect to remote sensing, such as navigation and surveillance, and the airborne receivers, depending on their working scenario, could be forced to gather data from arbitrary directions. On this basis a geometric analysis is carried out to define image resolutions and to individuate best/worst illumination conditions of the spaceborne transmitter.

关键词： image resolution Lead signal resolution Bandwidth Low earth orbit satellites

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A Review of Motion Segmentation: Approaches and Major Challenges

A Review of Motion Segmentation: Approaches and Major Challe...

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International Multidisciplinary Information Technology and Engineering conference (IMITEC)

作者： Jana Mattheus Hans Grobler Adnan M. Abu-Mahfouz University of Pretoria South Africa Council for Scientific and Industrial Research South Africa

ISBN: (数字)9781728195209

ISBN: (纸本)9781728195216

Motion segmentation has applications in, amongst others, robotics, traffic monitoring, sports analysis, inspection, video surveillance, compression, and video indexing. However, the performance of most methods is limited compared to human capabilities. Based on extensive literature the following challenges remain: occlusions, temporary stopping, missing data, and segmenting multiple objects. In this paper, several popular and state-of-the-art methods were reviewed, with the focus on the most important attributes. These methods were classified according to the main approach taken, namely image Difference, Optical Flow, wavelet, Statistical, Layers, Manifold Clustering, Template Matching, and Deep Learning. The investigated methods are compared and major research challenges are highlighted. Based on the review, improvements are identified as a basis for future research.

关键词： Manifolds Computer vision Motion segmentation Video surveillance Trajectory Video signal processing Sports

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Benchmarking validity procedures for unsupervised fuzzy pattern classification

Benchmarking validity procedures for unsupervised fuzzy patt...

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IEEE International conference on Multimedia Computing and Systems (ICMCS)

作者： Abdellah Lachhab Abdelaziz Bouroumi Ben M'sik Faculty of Science Hassan II Mohamedia University UH2M Casablanca Morocco

In this paper, we present some numerical results of an experimental study of the problem of automatic determination of the number of clusters in unsupervised fuzzy clustering. The study was conducted using the well-known fuzzy c-means algorithm and four associated validity criteria that we applied to illustrative examples of artificial and real data sets. We will mainly focus on the risk of validating bad solutions or rejecting good ones. This risk is inherent to traditional validity procedures, which generally make use of a single criterion, and a multi-criteria procedure is proposed in order to avoid it in real-world applications.

关键词： Pattern classification Clustering algorithms Fuzzy sets Unsupervised learning Pattern recognition Laboratories Guidelines Testing signal processing image processing

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