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Asilomar conference on signals, Systems, and Computers

作者： Marcin Iwanow Nikola Vucic Samer Bazzi Jian Luo Wolfgang Utschick Huawei Technologies German Research Center Munich Germany Associate Institute for Signal Processing Technische Universität München (TUM) Germany

We consider a point-to-point mmWave link with hybrid digital-analog transceivers, where the analog stage is realized with a network of phase shifters. Moreover, we concentrate on a case particularly relevant from the practical perspective. Namely, we constrain the analog stage such that disjoint antenna subarrays are processed separately in the analog domain. In this work, a novel precoding and combining strategy is developed. In order to exploit the inherent modularity of the analog stage in the subarray architectures, we separate the design of the digital and analog processing and concentrate on the latter. Namely, for the design of the analog stage we propose a subspace-arrangement based greedy algorithm.

关键词： Radio frequency Resource management Transmitters Precoding Computer architecture Antenna arrays

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SAR ground moving target's along-track velocity estimation in the complex image domain via SoWVD

SAR ground moving target's along-track velocity estimation i...

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IET International Radar conference 2018, IRC 2018

作者： Huang, Zuzhen Ding, Zegang Meng, Canzhen Ge, Yinchao School of Information and Electronics Beijing Institute of Technology Beijing100081 China Air Force Early Warning Academy PLA Wuhan430019 China Wuhan Second Ship Design and Research Institute Wuhan430205 China

A ground moving target is always defocused in the synthetic aperture radar (SAR) image domain due to the along-track velocity. In the image domain, a moving target's complex response along the azimuth direction can be modelled as a linear frequency-modulated signal, therefore, its Doppler rate, as well as the along-track velocity, can be estimated based on the recently proposed second-order Wigner-Ville (SoWVD) distribution transform. The proposed method has a low computational complexity without the search procedure and can be well combined with the SAR ground moving target detection algorithms in image domain, where the signal to clutter-plus-noise ratio is higher than other domains. Finally, the effectiveness of this method is verified with some numerical experiments. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Synthetic aperture radar

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Use of Gabor filters and Deep Networks in the Segmentation of Retinal Vessel Morphology 15

Use of Gabor filters and Deep Networks in the Segmentation o...

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conference on Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XV

作者： Leopold, Henry A. Orchard, Jeff Zelek, John Lakshminarayanan, Vasudevan Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Univ Waterloo David R Cheriton Sch Comp Sci Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781510605770;9781510605787

The segmentation of retinal morphology has numerous applications in assessing opthalmologic and cardiovascular disease pathologies. The early detection of many such conditions is often the most effective method for reducing patient risk. Computer aided segmentation of the vasculature has proven to be a challenge, mainly due to inconsistencies such as noise, variations in hue and brightness that can greatly reduce the quality of fundus images. Accurate fundus and/or retinal vessel maps give rise to longitudinal studies able to utilize multimodal image registration and disease/condition status measurements, as well as applications in surgery preparation and biometrics. This paper further investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using the Digital Retinal images for Vessel Extraction database, a standardized set of fundus images used to gauge the effectiveness of classification algorithms. The CNN has a feed-forward architecture and varies from other published architectures in its combination of: max-pooling, zero-padding, ReLU layers, batch normalization, two dense layers and finally a Softmax activation function. Notably, the use of Adam to optimize training the CNN on retinal fundus images has not been found in prior review. This work builds on prior work of the authors, exploring the use of Gabor filters to boost the accuracy of the system to 0.9478 during post processing. The mean of a series of Gabor filters with varying frequencies and sigma values are applied to the output of the network and used to determine whether a pixel represents a vessel or non-vessel.

关键词： Retinal image Analysis Gabor Filters Convolutional Neural Networks Deep Learning

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A Methodology to Estimate the Energy Consumption and processing Time for image processing Algorithms in Advanced Driver Assistance Systems

A Methodology to Estimate the Energy Consumption and Process...

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ARCS 2017;30th International conference on Architecture of Computing Systems

作者： Christian Hartmann Christian Widerspick Dietmar Fey Department of Computer Science Chair of Computer Architecture Friedrich-Alexander-University Erlangen-Nurnberg (FAU)

Recent trends in the automotive sector led to the use of more computing architectures inside the car. The reason for this increase is the usage of new advanced driver assistance systems (ADAS) in order to avoid human made accidents. Headed by Tesla, BMW and Mercedes all vast automobile manufacturer attempt to integrate ADAS systems inside their cars. With increasing system complexity and increasing costs a methodology to determine the functional properties and also to predict the non-functional properties is necessary in the early project stages. In contrast to systems with standard PC solutions, image processing advanced driver assistance systems are part of the embedded field. These systems have strict constraints such as processing time and energy consumption. Nowadays, simulation environments are used to consider the non-functional properties in the early stages of the design phase. These simulators are often inaccurate and have long simulation time for complex systems. In our work we introduce a novel methodology, based on the reuse distance theory to estimate non-functional properties for image processing algorithms in advanced driver assistance systems.

关键词： advanced driver assistance systems (ADAS) image processing algorithm processing time energy consumption Driver Assistance Systems functional characteristics Cars design phases

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image-based algorithm for the catheter recognition based on GLCM 28

Image-based algorithm for the catheter recognition based on ...

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28th International conference on Computer Graphics and Vision, GraphiCon 2018

作者： Danilov, V.V. Skirnevskiy, I.P. Manakov, R.A. Gerget, O.M. Melgani, F. Medical Devices Design Laboratory Tomsk Polytechnic University Tomsk Russia Signal Processing and Recognition Laboratory University of Trento Trento Italy

The focus of this study was to develop an image-based algorithm for the catheter detection. Epicardial full-volume 3D echocardiography datasets were used as an input data of the algorithm. In total, 9 datasets consisted of 15 three-dimensional timeframes were processed. To correctly detect the catheter, the feature-based approach was applied to recognition the catheter within the 3D echocardiography datasets. The algorithm based on gray-level co-occurrence matrix (GLCM) was applied as a feature extraction technique. Once the GLCM was computed, we obtained correlation, contrast, homogeneity and energy features. Then we applied feature thresholds to the catheter detection. These thresholds were obtained using Support Vector Machine (SVM) with the linear kernel function and standardization the predictor data. The average segmentation and recognition accuracies of the algorithm equal 94.16% and 87.2% respectively. The processing time for one 2D slice and one 3D dataset are equal to 9±0.2 milliseconds and 1.96±0.045 seconds, respectively. Though the algorithm is not time-consuming for 2D mode, it is still complicated to apply it for real-time surgery in 3D mode. © GraphiCon 2018 - 28th International conference on Computer Graphics and Vision. All rights reserved.

关键词： Catheters

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Key technologies of GNSS/INS/VO deep integration for UGV navigation in urban canyon

Key technologies of GNSS/INS/VO deep integration for UGV nav...

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11th Asian Control conference (ASCC)

作者： Wang Meiling Li Yafeng Feng Guoqiang Yang Yi Liu Tong Xuan Xiao Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Beijing Inst Technol State Key Lab Complex Syst Intelligent Control & Beijing 100081 Peoples R China

ISBN: (纸本)9781509015733

As a new emerging integrated navigation technology, the GNSS/INS/VO deep integration system can fully leverage the synergistic and complementary characteristics of the three involved subsystems to achieve cost reduction while improving navigation accuracy, availability, and robustness, by mutual aiding between subsystems. In this paper, firstly, based on a brief review of the technical background and research status of the GNSS/INS/VO deep integration technology, the processing flows of this deep integration mode in both signal and information domains are analyzed, and its performance advantages are summarized. Then, the top-level technology roadmap of the GNSS/INS/VO deep integration for UGV navigation in the urban canyon is presented, and several key technical issues from scheme demonstration to engineering implementation are explored. At last, the short and medium term development prospects of the GNSS/INS/VO deep integration are envisaged. The proposed research ideas and system design concept for GNSS/INS/VO deep integration could be used as a reference for relevant technicians in navigation field.

关键词： Global navigation satellite system Receivers image processing Data integration Extraterrestrial measurements Robustness

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Hybridization of RSA and AES algorithms for authentication and confidentiality of medical images

Hybridization of RSA and AES algorithms for authentication a...

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International conference on Communications and signal processing

作者： Santhosh Kumar B.J. Anjali Nair Roshni Raj V.K. Amrita School of Arts and Sciences Mysuru Campus Amrita Vishwa Vidyapeetham Amrita University Coimbatore Tamil Nadu IN Amrita School of Arts and Sciences Mysuru Campus Amrita Vishwa Vidyapeetham Amrita University India

image security is an essential part of communication through network. Nowadays the use of network and transmission of images has been widely increased. These images can be attacked by intruders and destroy the quality of the images or modified the images for illegal use. Considering these issues the proposed system ensuring the confidentiality, integrity and authentication of images using symmetric and asymmetric key cryptographic algorithm. Which make use of hybridization of two techniques i.e., RSA and AES for authentication and confidentiality. For improving the image integrity proposed system implemented image watermarking using LSB hiding algorithm. Watermarking is the process of hiding one image into another for copyright protection. RSA will be used for key generation and once key get generated, using AES algorithm watermarked image will be encrypted and send through a network. The receiving end the image will be decrypted and retrieved original watermark image.

关键词： Watermarking Encryption Biomedical imaging signal processing algorithms Algorithm design and analysis

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design Framework for General Purpose Object Recognition on a Robotic Platform 6

Design Framework for General Purpose Object Recognition on a...

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IEEE International conference on Communication and signal processing (ICCSP)

作者： Tenguria, Rajanikant Parkhedkar, Saurabh Modak, Nilesh Madan, Rishikesh Tondwalkar, Ankita Vidyalankar Inst Technol Dept Elect & Telecommun Engn Bombay 400039 Maharashtra India

ISBN: (纸本)9781509038008

The advancement in the broader field of Computer Vision is consequential, through past few decades. Therefore, a considerable improvement in object detection and tagging using convolutional neural networks has given way to accurate yet complex methods, which can identify objects in real-time. However, the growth in the area of implementing the algorithms on low powered portable devices has been relatively slow. This paper aims to converge the fields of computer vision and robotics, focusing on implementation of image description applications on an embedded system platform. We aim to integrate Neural Network powered object recognition system 'YOLO v2' with a robotic platform to explore the potential applications in the advancing domain of service and personal robotics.

关键词： Convolutional Neural Networks Robotics Object Recognition

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Group metropolis sampling

Group metropolis sampling

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European signal processing conference (EUSIPCO)

作者： Luca Martino Víctor Elvira Gustau Camps-Valls Image Processing Laboratory Universitat de València (Spain) IMT Lille Douai CRISTAL (UMR 9189) Villeneuve d’ Ascq (France)

Monte Carlo (MC) methods are widely used for Bayesian inference and optimization in statistics, signal processing and machine learning. Two well-known class of MC methods are the Importance Sampling (IS) techniques and the Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce the Group Importance Sampling (GIS) framework where different sets of weighted samples are properly summarized with one summary particle and one summary weight. GIS facilitates the design of novel efficient MC techniques. For instance, we present the Group Metropolis Sampling (GMS) algorithm which produces a Markov chain of sets of weighted samples. GMS in general outperforms other multiple try schemes as shown by means of numerical simulations.

关键词： Monte Carlo methods signal processing algorithms Markov processes Algorithm design and analysis signal processing Probability density function Europe

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