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A novel template-based multimedia processor array and its toolset

A novel template-based multimedia processor array and its to...

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International conference on Electrical and Electronics Engineering, ELECO

作者： Mehmet Tükel Arda Yurdakul Berna Örs Department of Electronics and Communication Engineering Istanbul Technical University Department of Computer Engineering Boğaziçi University

In this paper, we propose a template-based multimedia processor array and its design framework. The configurable processor array is designed for low-cost, low-power image/ video processing applications. Each processor in the array is template-based and implemented by considering the nature and specifications of image/video processing domain. The framework can set the size of the network and the parameters of the building blocks of each processor. Hence, the generated architecture occupies only the necessary amount of logic. To show the scalability and the performance of the design, different instances of the architecture implementing four test applications are generated. We have obtained better or comparable results in terms of energy consumption, throughput and area occupation compared to that of the similar architectures in literature.

关键词： Computer architecture Registers Parallel processing Hardware image processing Field programmable gate arrays Software

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Optimal design of Sparse MIMO Arrays for Near-Field Ultrawideband Imaging

Optimal Design of Sparse MIMO Arrays for Near-Field Ultrawid...

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European signal processing conference

作者： M. Burak Kocamis Figen S. Oktem Department of Electrical and Electronics Engineering Middle East Technical University Cankaya Ankara Turkey

Near-field ultrawideband imaging is a promising remote sensing technique in various applications such as air-port security, surveillance, medical diagnosis, and through-wall imaging. Recently, there has been increasing interest in using sparse multiple-input-multiple-output (MIMO) arrays to reduce hardware complexity and cost. In this paper, based on a Bayesian estimation framework, an optimal design method is presented for two-dimensional MIMO arrays in ultrawideband imaging. The optimality criterion is defined based on the image reconstruction quality obtained with the design, and the optimization is performed over all possible locations of antenna elements using an algorithm called clustered sequential backward selection algorithm. The designs obtained with this approach are compared with that of some commonly used sparse array configurations in terms of image reconstruction quality for various noise levels.

关键词： Antenna arrays MIMO image reconstruction Imaging Antenna measurements Transmitting antennas

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CNN architectures for large-scale audio classification

CNN architectures for large-scale audio classification

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IEEE International conference on Acoustics, Speech and signal processing

作者： Shawn Hershey Sourish Chaudhuri Daniel P. W. Ellis Jort F. Gemmeke Aren Jansen R. Channing Moore Manoj Plakal Devin Platt Rif A. Saurous Bryan Seybold Malcolm Slaney Ron J. Weiss Kevin Wilson Google Inc. New York USA

ISBN: (纸本)9781509041183

Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. We examine fully connected Deep Neural Networks (DNNs), AlexNet [1], VGG [2], Inception [3], and ResNet [4]. We investigate varying the size of both training set and label vocabulary, finding that analogs of the CNNs used in image classification do well on our audio classification task, and larger training and label sets help up to a point. A model using embeddings from these classifiers does much better than raw features on the Audio Set [5] Acoustic Event Detection (AED) classification task.

关键词： Acoustic Event Detection Acoustic Scene Classification Convolutional Neural Networks Deep Neural Networks Video Classification

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Fire image detection based on clustering data mining techniques 28

Fire image detection based on clustering data mining techniq...

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conference on image and signal processing for Remote Sensing XXVIII

作者： Harkat, H. Nascimento, J. Bernardino, A. Ahmed, H. Farhana Thariq Inst Telecomunicacoes Ave Rovisco Pais 1 P-1049001 Lisbon Portugal NOVA Univ Lisbon Ctr Technol & Syst CTS Uninova P-2829516 Monte De Caparica Portugal IPL Inst Super Engn Lisboa Lisbon Portugal Univ Lisbon Inst Syst & Robot Inst Super Tecn Lisbon Portugal Vellore Inst Technol Sch Comp Sci & Engn Chennai 600127 Tamil Nadu India

ISBN: (纸本)9781510655386;9781510655379

The number of forest fires is growing exponentially with globalization negative impacts and industry evolution. The firefighters are unable to attend fire sources in the desired elapse time. Hence a huge number of forests are destroyed yearly. The statics demonstrate horrible prediction in a time interval of less than ten years. Necessary action and evolution plans must be established to save the globe from an invasive destruction due to the disappear of green areas and consequent disequilibrating ecosystem effects. The obvious idea is to take advantage of current evolution in informatic systems and robotic field, to develop a distance controllable device to scan areas classified as high risk in the vulnerable season (hot season). The first step is to design a machine learning accurate approach to detect fire area on pictures acquired by probable drone or intelligent systems, responsible of the scanning task. Through literature, several approaches were developed treating pictures that are more with afront view of the flames. Training a machine learning algorithm with such pictures with huge areas of flames is feasible. Nonetheless, treating aerial images is not a very easy approach. A deep analysis of the chosen feature engineering technique and machine learning model is required. The current paper accesses the performance of wavelet-based feature extraction technique within different traditional clustering techniques and ranking methods. The results were accessed using different metrics, to show the effectiveness of the approach, namely sensitivity specificity, precision, recall, f-measure, and g-mean.

关键词： forest fire feature engineering ranking methods clustering techniques metrics

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Sobel filter operation in image processing via stochastic arithmetic-logic unit design

Sobel filter operation in image processing via stochastic ar...

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IEEE signal processing and Communications Applications (SIU)

作者： Sercan Aygün Mustafa Altun Ece Olcay Güneş Elektronik ve Haberleşme Mühendisliği Bölümü İstanbul Teknik Üniversitesi İstanbul Türkiye Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi İstanbul Türkiye

ISBN: (纸本)9781509064953

With the increase of technological developments, the speed limit of the processors that have emerged has accelerated the reduction of nanotechnological solutions of transistors into atomic dimensions from nanometers. Physical systems in which stochastic computation is critical instead of deterministic computation by taking action from atomic behavior are discussed. For this reason, as an interdisciplinary study, this paper will discuss the application of the arithmetic-logic unit in stochastic behavior for the design issues and image processing applications. The logic level design made by considering the design constraints will be used during known image filtering operations. Probabilistic pixel values in binary that sent to the input of the arithmetic logic unit will be used in the Sobel image processing operator. The images are processed with both conventional filter and stochastic filter, then the results obtained will be given visually.

关键词： Field programmable gate arrays image edge detection Transistors Nanoelectronics PSNR Computers

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On classification of distorted images with deep convolutional neural networks

On classification of distorted images with deep convolutiona...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Yiren Zhou Sibo Song Ngai-Man Cheung Singapore University of Technology and Design Singapore

ISBN: (纸本)9781509041183

image blur and image noise are common distortions during image acquisition. In this paper, we systematically study the effect of image distortions on the deep neural network (DNN) image classifiers. First, we examine the DNN classifier performance under four types of distortions. Second, we propose two approaches to alleviate the effect of image distortion: re-training and fine-tuning with noisy images. Our results suggest that, under certain conditions, fine-tuning with noisy images can alleviate much effect due to distorted inputs, and is more practical than re-training.

关键词： image blur image noise deep convolutional neural networks re-training fine-tuning image noise image blur image DISTORTION fine tuning images Noisy image Neural network image samples

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1-bit Massive MU-MIMO Precoding in VLSI

1-bit Massive MU-MIMO Precoding in VLSI

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IEEE Journal on Emerging and Selected Topics in Circuits and Systems

作者： Castañeda, Oscar Jacobsson, Sven Durisi, Giuseppe Coldrey, Mikael Goldstein, Tom Studer, Christoph School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States Ericsson Research Gothenburg417 56 Sweden Chalmers University of Technology Gothenburg412 58 Sweden Department of Computer Science University of Maryland College ParkMD20742 United States

Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in fifth-generation (5G) wireless systems as it offers significant improvements in spectral efficiency compared to existing multi-antenna technologies. The presence of hundreds of antenna elements at the base station (BS), however, results in excessively high hardware costs and power consumption, and requires high interconnect throughput between the baseband-processing unit and the radio unit. Massive MU-MIMO that uses low-resolution analog-to-digital and digital-to-analog converters (DACs) has the potential to address all these issues. In this paper, we focus on downlink precoding for massive MU-MIMO systems with 1-bit DACs at the BS. The objective is to design precoders that simultaneously mitigate MU interference and quantization artifacts. We propose two nonlinear 1-bit precoding algorithms and corresponding very large-scale integration (VLSI) designs. Our algorithms rely on biconvex relaxation, which enables the design of efficient 1-bit precoding algorithms that achieve superior error-rate performance compared with that of linear precoding algorithms followed by quantization. To showcase the efficacy of our algorithms, we design VLSI architectures that enable efficient 1-bit precoding for massive MU-MIMO systems, in which hundreds of antennas serve tens of user equipments. We present corresponding field-programmable gate array (FPGA) reference implementations to demonstrate that 1-bit precoding enables reliable and high-rate downlink data transmission in practical systems. © 2011 IEEE.

关键词： MIMO systems 5G mobile communication systems Analog to digital conversion Antennas Codes (symbols) Digital to analog conversion Feedback control Field programmable gate arrays (FPGA) Integrated circuit design Logic gates signal receivers Telecommunication repeaters VLSI circuits Biconvex relaxation Multiuser multiple input multiple outputs (MU MIMO) Precoding quantization Very large scale integrations (VLSI)

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design of a Color Palette Based image Steganography Algorithm for Fractal images 2

Design of a Color Palette Based Image Steganography Algorith...

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2nd IEEE International conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Patel, Hetal N. Khant, Dipanjali R. Prajapati, Darshana AD Patel Inst Technol Elect & Commun Dept Anand Gujarat India M&B Patel Womens Inst Engn Math Dept Anand Gujarat India

ISBN: (纸本)9781509044429

image steganography is a smart technique of embedding the secret information into the cover image without any visual loss. As fractal image represents self-similar patterns, more number of bits can be embedded. A color palette based image steganography algorithm for the iterated Julia-set fractal image is proposed. The color palette is created and sorted based on the illumination values of the pixels. The palette is being scanned for embedding the secret bit, and the palette index is modified based on the secret bit's value. For improving the robustness of the algorithm, a random pixel selection technique is suggested and implemented effectively. The proposed algorithm gives maximum peak signal to noise ratio (PSNR), up to the number 61, and Normalized Correlation (NC) of 0.999 for approximately 50 images.

关键词： Steganography fractals palette based images Julia set NC PSNR

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3D MODEL GENERATION USING OBLIQUE imageS ACQUIRED BY UAV

3D MODEL GENERATION USING OBLIQUE IMAGES ACQUIRED BY UAV

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European conference on Free and Open Source Geospatial Technologies (FOSS4G-Europe)

作者： Lingua, A. Noardo, F. Spano, A. Sanna, S. Matrone, F. Politecn Torino Dept Environm Land & Infrastruct Engn DIATI Corso Duca Abruzzi 24 I-10129 Turin Italy Politecn Torino Dept Architecture & Design DAD Viale Mattioli 39 I-10125 Turin Italy

In recent years, many studies revealed the advantages of using airborne oblique images for obtaining improved 3D city models (including facades and building footprints). Here the acquisition and use of oblique images from a low cost and open source Unmanned Aerial Vehicle (UAV) for the 3D high-level-of-detail reconstruction of historical architectures is evaluated. The critical issues of such acquisitions (flight planning strategies, ground control points distribution, etc.) are described. Several problems should be considered in the flight planning: best approach to cover the whole object with the minimum time of flight;visibility of vertical structures;occlusions due to the context;acquisition of all the parts of the objects (the closest and the farthest) with similar resolution;suitable camera inclination, and so on. In this paper a solution is proposed in order to acquire oblique images with one only flight. The data processing was realized using Structure-from-Motion-based approach for point cloud generation using dense image-matching algorithms implemented in an open source software. The achieved results are analysed considering some check points and some reference LiDAR data. The system was tested for surveying a historical architectonical complex: the "Sacro Monte di Varallo Sesia" in north-west of Italy. This study demonstrates that the use of oblique images acquired from a low cost UAV system and processed through an open source software is an effective methodology to survey cultural heritage, characterized by limited accessibility, need for detail and rapidity of the acquisition phase, and often reduced budgets.

关键词： UAV oblique images flight plan SfM cultural heritage open source

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Precise design-Based Defect Characterization and Root Cause Analysis 31

Precise Design-Based Defect Characterization and Root Cause ...

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31st conference on Metrology, Inspection, and Process Control for Microlithography

作者： Xie, Qian Venkatachalam, Panneerselvam Lee, Julie Chen, Zhijin Zafar, Khurram GLOBALFOUNDRIES Santa Clara CA 95054 USA Anchor Semicond Santa Clara CA USA

ISBN: (数字)9781510607422

ISBN: (纸本)9781510607415;9781510607422

As semiconductor manufacturing continues its march towards more advanced technology nodes, it becomes increasingly important to identify and characterize design weak points, which is typically done using a combination of inline inspection data and the physical layout (or design). However, the employed methodologies have been somewhat imprecise, relying greatly on statistical techniques to signal excursions. Therefore, common operations such as background-based binning that are designed to identify frequently failing patterns cannot reliably identify specific weak patterns. They can only identify an approximate set of possible weak patterns, but within these sets there are many perfectly good patterns. Additionally, characterizing the failure rate of a known weak pattern based on inline inspection data also has a lot of fuzziness. SEM (Scanning Electron Microscope) Review attempts to come to the rescue by capturing high resolution images of the regions surrounding the reported defect locations, but SEM images are reviewed by human operators and the weak patterns revealed in those images must be manually identified and classified. Compounding the problem is the fact that a single Review SEM image may contain multiple defective patterns and several of those patterns might not appear defective to the human eye. In this paper we describe a significantly improved methodology that brings advanced computer image processing and design-overlay techniques to better address the challenges posed by today's leading technology nodes. Specifically, new software techniques allow the computer to analyze Review SEM images in detail, to overlay those images with reference design to detect every defect that might be present in all regions of interest within the overlaid reference design (including several classes of defects that human operators will typically miss), to obtain the exact defect location on design, to compare all defective patterns thus detected against a library of known

关键词： SEM to design Overlay Region of Interest design-Based Detection Root Cause Analysis design-Based Pattern Classification Inline Defect to Weakpoint Correlation Weakpoint Ranking

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