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Rule-Based Fuzzy Systems with Weighted Power Mean Firing Operator as Universal Approximators

Rule-Based Fuzzy Systems with Weighted Power Mean Firing Ope...

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IEEE International conference on Fuzzy Systems

作者： John T. Rickard Janet Aisbett Jerry M. Mendel Distributed Infinity Inc. School of Science and IT University of Newcastle Signal and Image Processing Institute Ming Hsieh Dept. of Electrical Engineering University of Southern California

ISBN: (纸本)9781467315074

Certain classes of fuzzy rule-based systems have been shown to be universal approximators, capable of approximating any continuous mapping on a compact subset of the domain. In previous cases, this property has been proven for fuzzy systems employing t-norms to determine the firing level of each rule. In this paper, we prove that use of the weighted power mean to determine rule firing levels also results in a universal approximator. While it is only a t-norm in certain special cases, the weighted power mean is a more general aggregation operator, capable of providing greater logical flexibility in a rule. This will be of particular interest in computing with words (CWW) applications, where such flexibility is needed the better to mimic human reasoning.

关键词： Fuzzy rule-based systems Aggregation operators Universal approximation Computing with words Fuzzy systems Fire FIRING Universal Rule Flexibility Power (Psychology) Energy sources Operators fuzzy rule-based system

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E-discover State-of-the-art Research Trends of Deep Learning for Computer vision

E-discover State-of-the-art Research Trends of Deep Learning...

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IEEE International conference on Systems, Man and Cybernetics

作者： Annie A. S. Li Amy J. C. Trappey Charles v. Trappey C. Y. Fan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Distinguished Professor in the Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Department of Management Science National Chiao Chiao Tung Tung University Hsinchu Taiwan Science and Technology Policy and Information Center National Applied Research Laboratory Taipei Taiwan

Computer vision (Cv) attempts to mimic human eyes for image processing and identifications of detailed visual information, such as object positions, features of appearances, and even human emotions and behaviors. In this research, more than one hundred literatures, relating to applying deep learning (DL) methodologies in advanced computer visions (2010~2018), are reviewed and analyzed. The objective is to discover the state-of-the-art DL methods, topics, and trends for Cv and their practical applications. DL algorithms aim at representing multi-levels of distributed neural networks. Because of the enhancement of high speed computational power, DL modeling, based on accumulated big data analytics, has found practical applications for non-supervised intelligent decision supports, such as detection of product defects and prognosis of machine malfunctions based on real-time signal or feature data analyses. There are a vast number of literature, describing DL related researches, developments, and implementations for problem solving. For the comprehensive mining of the related literature, we integrate Latent Dirichlet Allocation (LDA), K-means (Clustering), and normalized term frequency-inverse document frequency (NTF-IDF) approaches to discover, or called technology mining, of the major trends in DL for computer visions, specifically for key applications in object detection, semantic segmentation, image retrieval, and human pose estimation.

关键词： Machine learning Computer vision Market research Text mining Resource management Radio spectrum management

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Analysis of Multispectral image Using Discrete wavelet Transform

Analysis of Multispectral Image Using Discrete Wavelet Trans...

引用

International conference on Advanced Computing and Communication Technologies

作者： Hari Kumar Singh S. K. Tomar Pooja Singh Department of Electronics and Communication Engineering IETM.J.P Rohilkhand University R. B. M. I. Group of Institution

ISBN: (纸本)9781467359658

In this paper we have analyzed the discrete wavelet transform of multispectral image of Bareilly region using MatLab tool. The wavelet transform is one of the most useful computational tools for a variety of signal and image processing applications. The wavelet transform is used for the compression of digital image because smaller data are important for storing images using less memory and for transmitting images faster and more reliably. wavelet transforms are useful for images to reduce unwanted noise and blurring. A discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled. A key advantage it has over Fourier transforms is temporal resolution: it captures both frequency and time domain information.

关键词： wavelet wavelet Transform DWT Compression Techniques

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An Optimization Method of WebP images Lossy Compression Algorithm for FPGAs

An Optimization Method of WebP Images Lossy Compression Algo...

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Yaqian Zhao Zhenhua Guo Baoyu Fan Kai Gao Li Wang Fang Cao Inspur Electronic Information Industry Co. Ltd. Jinan China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

To improve the efficiency of WebP images lossy compression algorithm for heterogeneous accelerating based on FPGAs in data center server, this paper proposed an optimization method of WebP image lossy compression algorithm for FPGAs. By adopting the optimization method of this paper, the overall throughput performance of WebP heterogeneous acceleration solution based on OpenCL language can be up to 281MPixel/s. The energy efficiency ratio is 2.29x higher than Intel Xeon E5-2690v3 processor. Compare with the industry-leading WebP heterogeneous acceleration solution of Xilinx and CTAccel, the throughput performance of this paper is 2.5x better than Xilinx and 1.8x better than CTAccel. Finally, this paper improves the utilization of RAM resources according to the characteristics of the RAM block in the FPGA.

关键词： Field programmable gate arrays Compression algorithms image coding Pipeline processing Quantization (signal) Acceleration Transforms

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Sampling Of 3d Point Cloud via Gershgorin Disc Alignment

Sampling Of 3d Point Cloud Via Gershgorin Disc Alignment

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IEEE International conference on image processing

作者： Chinthaka Dinesh Gene Cheung Fen Wang Ivan v. Bajić School of Engineering Science Simon Fraser University Burnaby Canada Dept of EECS York University Toronto Canada State Key Laboratory of ISN Xidian University China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Point cloud-a collection of geometric samples of a physical object in 3D space-can be very large in size, which entails a large computation cost for many imaging applications. In this paper, we reduce the size of a point cloud towards a more compact representation via optimal sub-sampling. Specifically, we first derive a sampling objective that maximizes the stability (maximizes the smallest eigenvalue λ min (B) of a coefficient matrix B = H T H + μL) of a linear system super-resolving a sub-sampled point cloud. To circumvent eigen-decomposition, we maximize instead a lower bound λ min - (B) using a fast graph sampling scheme called Gershgorin disc alignment (GDA) based on the well-known Gershgorin circle theorem. However, GDA requires that the disc left-ends of real matrix L are initially aligned at the same value, which is not the case for point clouds. Orthogonally, we recently derived a matrix theorem proving that disc left-ends of a generalized graph Laplacian matrix for a balanced and irreducible signed graph can be perfectly aligned via a similarity transform using the matrix's first eigenvector. Leveraging this work, we first interpret L as a generalized graph Laplacian matrix and balance the underlying graph. We then align disc left-ends of the resulting generalized graph Laplacian of the balanced graph using its first eigenvector, in order to employ GDA for point cloud sampling. Experiments show that our sampling method outperforms competing methods in super-resolved point cloud quality.

关键词： Three-dimensional displays Laplace equations image resolution Eigenvalues and eigenfunctions signal resolution Optimization image reconstruction

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Nonlocal Two Dimensional Denoising of Frequency Specific Chirp Evoked ABR Single Trials

Nonlocal Two Dimensional Denoising of Frequency Specific Chi...

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

作者： J. Kristof Schubert Tanja Teuber Gabriele Steidl Daniel J. Strauss Farah I. Corona-Strauss Systems Neuroscience & Neurotechnology Unit Saarland UniversityFaculty of Medicine Neurocenter Building 90.5 D-66421 Homburg/SaarGermany Mathematical Image Processing and Data Analysis Technical University Kaiserslautern Felix Klein Zentrum D-67663 Kaiserslautern Germany

ISBN: (纸本)9781457717871

Recently, we have shown that denoising evoked potential (EP) images is possible using twodimensional diffusion filtering methods. This restoration allows for an integration of regularities over multiple stimulations into the denoising process. In the present work we propose the nonlocal means (NLM) method for EP image denoising. The EP images were constructed using auditory brainstem responses (ABR) collected in young healthy subjects using frequency specific and broadband chirp stimulations. It is concluded that the NLM method is more efficient than conventional approaches in EP imaging denoising, specially in the case of ABRs, where the relevant information can be easily masked by the ongoing EEG activity, i.e., signals suffer from rather low signal-to-noise ratio SNR. The proposed approach is for the a posteriori denoising of single trials after the experiment and not for real time applications.

关键词： stimulations experiment applications

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Comparison of Bone Mineral Densities Obtained From X Ray and Dexa images

Comparison of Bone Mineral Densities Obtained From X Ray and...

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2011 International conference on signal,image processing and applications（ICSIA 2011）

作者： R.Sivakumar R.Tamilselvi S.R.Saranya M.v.Supraja K.Pournam Department of Electronics and Communication Engineering RMK Engineering College

Osteoporosis is a disease of the bones that leads to increased risk of fracture in pelvic girdle,femur,vertebrae and carpal *** is most common in women after menopause where it is called post menopausal *** is a condition characterized by a decrease in the density of the bone,decreasing the strength and resulting in fragile *** that are affected by osteoporosis can break with relatively minor injury that normally would not cause a bone to *** spine,hips,ribs and wrists are common areas of bone fracture from osteoporosis although it can occur in almost any skeletal *** can be diagnosed by reduced bone mineral density,disrupted bone micro architecture and alteration in the amount and variety of proteins in *** our proposed work we developed an algorithm to diagnose the osteoporosis related changes in the femur bone of women with the help of X-Ray images by measuring the bone mineral density in *** we compare the bone mineral density obtained from the DEXA images with the density obtained from the conventional X-ray image.

关键词： Segmentation,Bone mineral density,dexa images

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Recognition of Hybrid Digital Watermarking Techniques using Digital image processing using Deep Learning Techniques

Recognition of Hybrid Digital Watermarking Techniques using ...

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Augmented Intelligence and Sustainable Systems (ICAISS), International conference on

作者： Chilumala Indira RM Noorullah Praveen Kumar Balguri Sowjanya Krishna Pinisetty Department of Computer Science and Engineering Institute of Aeronautical Engineerring Dundigal Hyderabad India Department of Aeronautical Engineering Institute of Aeronautical Engineerring Dundigal Hyderabad India Institute of Fundamental and Frontier Science University of Electronic Science and Technology of China Chengdu China

Digital watermarking is the procedure to identify the source and creator of the data. This is a form of digital media marker such as video, audio or image format. It helps to protect the data from various external unauthorized access. This is done through embedded digital information in the carrier signal to identify ownership and copyright protection. Security and privacy concerns need to be improved due to the rapid increase in the transmission and receiving of digital data. various sectors such as the navy, military, intelligence, and police are sending and receiving numerous data through online mode. The existing system utilizes Arnold map with QWT-DCT techniques which are unable to obtain invisibility in attack detection. To overcome the limitations of the existing system the proposed system is implemented. They are highly confidential and need to be secured and protected thus hybrid digital watermarking techniques such as nested forms of watermarking are employed. If the third parties tend to make any modification, then it is termed as an attack. The removal of digital watermarking by third parties through certain modifications are denoted through copyright protection application. For security applications and to avoid various types of attacks, Discrete wavelet Transform (DWT) and Non-sampled Contourlet Transform (NSCT) are employed. Security and privacy is obtained through the Quaternion Fourier Transform (QFT) based algorithm with human speech recognition. The pixel displacement with pixel encryption is enhanced to save the privacy of images. Digital watermarking requires security, robustness, watermarking keys and computational cost parameter. Thus to protect the data by neglecting various conventional attacks, digital watermarking techniques are implemented through deep convolutional neural networks.

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Convoy detection processing by using the hybrid algorithm (GMCPHD/vS-IMMC-MHT) and dynamic bayesian networks

Convoy detection processing by using the hybrid algorithm (G...

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International conference on Information Fusion

作者： Evangeline Pollard Benjamin Pannetier Michele Rombaut Information Processing and Modeling Department ONERA Image and Signal Department GIPSA-lab

ISBN: (纸本)9780982443804

Convoys are military objects of interests in certain applications like battlefield surveillance, that is why it is important to detect and track them in the midst of civilian traffic as part of the situation assessment. Our purpose is a process in two steps. The first is an original tracking algorithm appropriate for Ground Moving Target Indicator (GMTI) data based on the hybridization of a labeled GMCPHD (Gaussian Mixture Cardinalized Probability Hypothesis Density) and the vS-IMMC-MHT (variable Structure - Interacting Multiple Model with Constraints - Multiple Hypothesis Tracking): one is very efficient to estimate the number of targets and the other for the state estimates. Then, by using algorithm outputs and other data like video or SAR if they are available, vehicle aggregates are detected and their characteristic are introduced into a Dynamic Bayesian Network which processes the probability for an aggregate to be a convoy. Finally, the number of targets belonging to the convoy is evaluated. This process is tested on a complex simulated scenario, our tracking algorithm is compared to classical ones and used to compute the probability to have convoys.

关键词： Multitarget Tracking GMTI Convoy detection GMCPHD vS-IMMC-MHT Dynamic Bayesian network

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Advancements in video-Based Insect Tracking: A Bibliometric Analysis to A Short Survey 23

Advancements in Video-Based Insect Tracking: A Bibliometric ...

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Proceedings of the 2023 7th International conference on Advances in image processing

作者： Erick A. Adje Arnaud S. R. M. Ahouandjinou Gilles Delmaire Gilles Roussel Ratheil v. Houndji Unité de Recherche en Sciences Informatiques et Applications Université d'Abomey-Calavi Benin and Laboratoire d'Informatique Signal et Image de la Côte d'Opale Université du Littoral Cote d'Opale France Unité de Recherche en Sciences Informatiques et Applications Université d'Abomey-Calavi Benin Laboratoire d'Informatique Signal et Image de la Côte d'Opale Université du Littoral Cote d'Opale France

ISBN: (纸本)9798400708275

video-based insect tracking provides vital insights into insect behavior and ecology, enhancing our understanding of their movements and interactions. Therefore, examining trends in this field over the last few years is essential. This study aims to conduct a bibliometric analysis to unveil the growing interest in video-based insect tracking with a short review based on documents used for bibliometric analysis. To achieve this, 453 documents were extracted from Scopus on 12 June 2023. Only documents in English published between 2010 and 2023, resulting in a dataset of 318 documents, were analyzed. The findings illustrate a consistent growth in video-based insect research over the last years, with a significant peak in 2021, comprising 32 documents. The journal PLOS ONE stands out as the most productive source. The USA exhibited the most significant interest in video-based insect tracking over the last years. Keyword analysis reflects the multidisciplinary nature of insect tracking research. The review demonstrated that video-based insect tracking serves two primary objectives: pose estimation and trajectory information. However, the main challenge in video-based insect tracking is to preserve the identity of multiple individuals in situations involving occlusions or complex interactions.

关键词： bibliometric analysis computer vision insect movement behavior video tracking

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