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检索条件"任意字段=2017 Conference on Design and Architectures for Signal and Image Processing, DASIP 2017"

共 891 条记录，以下是701-710 订阅

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design of A Double-blockchain Structured Carbon Emission Trading Scheme with Reputation 34

Design of A Double-blockchain Structured Carbon Emission Tra...

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34th Youth Academic Annual conference of Chinese-Association-of-Automation (YAC)

作者： Liang, Xufeng Du, Yuhao Wang, Xu Zeng, Yuliang Wuhan Univ Technol Sch Automat Wuhan Peoples R China

ISBN: (纸本)9781728139364

This paper proposes a double-blockchain structured trading scheme (DBR-ETS) in carbon emission permits secondary market and introduces the enterprises' reputation, which is used to urge enterprises to actively invest in carbon emission reduction, and ultimately achieve carbon emission reduction in the overall society. The application of blockchain technology guarantees the security and privacy of distributed system. The confirmation chain and financial chain in the double-blockchain structure divide the transaction into two relatively independent processes, which can not only alleviate the transaction redundancy in the system but also improve the security of the system through the mutual verification of the two chains. The reputation-based transaction fee mechanism allows enterprises to promote their reputation by increasing investment in emission reduction. In the case study, we verified the superiority of the double-blockchain structure and the effect of the transaction fee mechanism on emission reduction.

关键词： carbon emission permits double-blockchain reputation mechanism design

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International conference on Communication and Computing Systems, ICCCS 2016

International Conference on Communication and Computing Syst...

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International conference on Communication and Computing Systems, ICCCS 2016

ISBN: (纸本)9781138029521

The proceedings contain 192 papers. The special focus in this conference is on Communication and Computing Systems. The topics include: Temporal effects in collaborative filtering for recommendation systems;study on the formation of wrinkles in the panel drawing operation using fem;metaheuristics: Modeling variant of ant colony optimization for image edge detection using self adaptive approach;improving medical image classification model using data mining technique;iris recognition using hybrid transform;simo and miso universal filters employing otra;modeling of brain tumor detection using image processing;improved advanced modified decision based unsymmetric trimmed median filter for removal of salt and pepper noise;threshold segmentation technique for tumor detection using morphological operator;fpga implementation of low power & high speed accurate ecg signal detection using dablms algorithm;robust vehicle detection and localization using normalized color illumination;digital image forgery detection using the wavelet decomposition and low level feature points;binary image reconstruction using the adaptive hybrid mechanism with swarm optimization;application of signal processing to optimize em attack on aes;resistorless realization of universal filter employing cciii and ota;face detection from digital images: A comparative study;improved iris biometric system by exploring iris texture features;feature extraction of hyperspectral face images using pca in nir;design and analysis of high gain-low power operational-amplifier for bio-medical applications;early detection of symptoms in tongue cancer through image processing;a study on adaptive wavelet technique for speckle noise removal;image enciphering using modified aes with secure key transmission;trust version of aasr.

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RATM: Recurrent Attentive Tracking Model 30

RATM: Recurrent Attentive Tracking Model

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Kahou, Samira Ebrahimi Michalski, Vincent Memisevic, Roland Pal, Christopher Vincent, Pascal Ecole Polytech Montreal Montreal PQ Canada Univ Montreal Montreal PQ Canada

ISBN: (纸本)9781538607336

We present an attention-based modular neural framework for computer vision. The framework uses a soft attention mechanism allowing models to be trained with gradient descent. It consists of three modules: a recurrent attention module controlling where to look in an image or video frame, a feature-extraction module providing a representation of what is seen, and an objective module formalizing why the model learns its attentive behavior. The attention module allows the model to focus computation on task-related information in the input. We apply the framework to several object tracking tasks and explore various design choices. We experiment with three data sets, bouncing ball, moving digits and the real-world KTH data set. The proposed Recurrent Attentional Tracking Model (RATM) performs well on all three tasks and can generalize to related but previously unseen sequences from a challenging tracking data set.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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The Method of RGBX Sub-pixel Architecture for Power Efficient Display 4

The Method of RGBX Sub-pixel Architecture for Power Efficien...

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IEEE International conference on Consumer Electronics - Taiwan (ICCE-TW)

作者： Yang, Hsueh-Yen Natl Taiwan Univ Grad Inst Elect Engn Taipei Taiwan

ISBN: (纸本)9781509040179

the Active Matrix Organic Light Emitting Device (AMOLED) currently apply four sub-pixels architecture, which include a red (R), green (G), blue (B) and additional (X) sub-pixel, which has high luminous efficiency to achieve a power efficient display. Therefore, a specified algorithm would be requested to indicate which pair of sub-pixels is lighting up. In this work, we propose an available method to implement the selection for the display of four sub-pixels configuration. Utilizing the property of the CIE-xy coordinate, a threshold value would be derived to perform RGBX sub-pixels selection. The proposed method can simplify the difficulty of conventional algorithm.

关键词： image color analysis Active matrix organic light emitting diodes Power demand Gray-scale Algorithm design and analysis Brightness

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Combining deep convolutional neural network and SVM to SAR image target recognition 10

Combining deep convolutional neural network and SVM to SAR i...

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Joint 10th IEEE International conference on Internet of Things, iThings 2017, 13th IEEE International conference on Green Computing and Communications, GreenCom 2017, 10th IEEE International conference on Cyber, Physical and Social Computing, CPSCom 2017 and the 3rd IEEE International conference on Smart Data, Smart Data 2017

作者： Gao, Fei Huang, Teng Wang, Jun Sun, Jinping Yang, Erfu Hussain, Amir School of Electronic and Information Engineering Beihang University Beijing China Space Mechatronic Systems Technology Laboratory Department of Design Manufacture and Engineering Management University of Strathclyde GlasgowG1 1XJ United Kingdom Cognitive Signal-Image and Control Processing Research Laboratory School of Natural Sciences University of Stirling StirlingFK9 4LA United Kingdom

ISBN: (纸本)9781538630655

To address the challenging problem on target recognition from synthetic aperture radar (SAR) images, a novel method is proposed by combining Deep Convolutional Neural Network (DCNN) and Support Vector Machine (SVM). First, an improved DCNN is employed to learn the features of SAR images. Then, a SVM is utilized to map the leant features into the output labels. To enhance the feature extraction capability of DCNN, a class of separation information is also added to the cross-entropy cost function as a regularization term. As a result, this explicitly facilitates the intra-class compactness and separability in the process of feature learning. Numerical experiments are performed on the Moving and Stationary Target Acquisition and Recognition (MSTAR) database. The results demonstrate that the proposed method can achieve an average accuracy of 99.15% on ten types of targets. © 2017 IEEE.

关键词： Synthetic aperture radar

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Impulsive Stabilization of Positive Systems with Time-varying Delays 13

Impulsive Stabilization of Positive Systems with Time-varyin...

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13th IEEE International conference on Control & Automation (ICCA)

作者： Hu, Meng-Jie Wang, Yan-Wu Li, Bo Hu, Xiao-Ya Wang, Xiao-Ping Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan Hubei Peoples R China China Three Gorges Univ Minist Educ Hubei Prov Collaborat Innovat Ctr New Energy Micr Yichang Hubei Peoples R China Northeast Elect Power Univ Sch Automat Engn Jilin 132012 Jilin Peoples R China

ISBN: (纸本)9781538626795

This study investigates the impulsive stabilization problem of positive systems with time-varying delays. A new time-varying weighted copositive Lyapunov function is constructed. Sufficient stabilization conditions on the upper and lower bounds of impulsive intervals are established using the convex combination technique. Under the proposed conditions, the positivity and exponential stability of the corresponding closed-loop system can be guaranteed. Based on the linear programming (LP) technique, a systematic design procedure is presented for the impulsive controller. Finally, a numerical example is provided to demonstrate the effectiveness of the theoretical result.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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designing efficient architectures for modeling temporal features with convolutional neural networks

Designing efficient architectures for modeling temporal feat...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Jordi Pons Xavier Serra Music Technology Group Universitat Pompeu Fabra Barcelona Spain

ISBN: (纸本)9781509041183

Many researchers use convolutional neural networks with small rectangular filters for music (spectrograms) classification. First, we discuss why there is no reason to use this filters setup by default and second, we point that more efficient architectures could be implemented if the characteristics of the music features are considered during the design process. Specifically, we propose a novel design strategy that might promote more expressive and intuitive deep learning architectures by efficiently exploiting the representational capacity of the first layer - using different filter shapes adapted to fit musical concepts within the first layer. The proposed architectures are assessed by measuring their accuracy in predicting the classes of the Ballroom dataset. We also make available1 the used code (together with the audio-data) so that this research is fully reproducible.

关键词： Convolutional neural networks deep learning music classification information retrieval Music information retrieval ARCHITECTURE Machine Learning Filters Neural network

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13th International conference on Intelligent Information Hiding and Multimedia signal processing, IIH-MSP 2017

13th International Conference on Intelligent Information Hid...

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13th International conference on Intelligent Information Hiding and Multimedia signal processing, IIH-MSP 2017

ISBN: (纸本)9783319638584

The proceedings contain 103 papers. The special focus in this conference is on Intelligent Information Hiding and Multimedia signal processing. The topics include: Extraction of EEG components based on time - frequency blind source separation;an algorithm for asymmetric clipping detection based on parameter optimization;automatic facial age estimate based on convolution neural network;the application of eye tracking in education;adaptive multiple description depth image coding based on wavelet sub-band coefficients;adaptive histogram shifting based reversible data hiding;design and implementation of network video encryption system based on STM32 and AES algorithm;implementation of a drone-based video streamer;response selection of interview-based dialog system using user focus and semantic orientation;development and evaluation of Julius-compatible interface for kaldi ASR;voice conversion from arbitrary speakers based on deep neural networks with adversarial learning;evaluation of nonlinear tempo modification methods based on sinusoidal modeling;towards an interrogation speech manipulation detection method using speech fingerprinting;detection of singing mistakes from singing voice;a study of audio watermarking method using non-negative matrix factorization for a duet of different instruments;a wind noise detection algorithm for monitoring infrasound using Smartphone as a sensor device;study on speech representation based on spikegram for speech fingerprints;embedding multiple audio data using information misreading technique;an automatic detection method for Morse signal based on machine learning and building of a practical monitoring system for the small wind turbine.

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13th International conference on Intelligent Information Hiding and Multimedia signal processing, IIH-MSP 2017

13th International Conference on Intelligent Information Hid...

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13th International conference on Intelligent Information Hiding and Multimedia signal processing, IIH-MSP 2017

ISBN: (纸本)9783319638553

The proceedings contain 103 papers. The special focus in this conference is on Intelligent Information Hiding and Multimedia signal processing. The topics include: A survey of reversible data hiding schemes based on two-dimensional histogram modification;steganographic image hiding schemes based on edge detection;a new data hiding strategy based on pixel-value-differencing method;data hiding scheme based on regular octagon-shaped shells;a web page watermarking method using hybrid watermark hiding strategy;integrated health check report analysis and tracking platform;a study of the multi-organization integrated electronic attendance system;a content analysis of mobile learning on constructivism theory;an independence mechanism design for the software defined device;an ontology-based herb therapy recommendation for respiration system;robust optimal control technology for multimedia signal processing applications;on the automatic construction of knowledge-map from handouts for MOOC courses;automated music composition using heart rate emotion data;inter-vehicle media distribution for driving safety;high-capacity ECG steganography with smart offset coefficients;compression-efficient reversible data hiding in zero quantized coefficients of JPEG images;using optical coherence tomography to identify of oral mucosae with 3D printing probe;novel approach of respiratory sound monitoring under motion;a general auto-alignment algorithm for three-degree freedom stage by local inverse information with regression method;initial phase of building up a portable multiple-wavelength biomedical sensing system and a new solution method for a class of fuzzy random bilevel programming problems.

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COMPLEXIS 2017 - Proceedings of the 2nd International conference on Complexity, Future Information Systems and Risk

COMPLEXIS 2017 - Proceedings of the 2nd International Confer...

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2nd International conference on Complexity, Future Information Systems and Risk, COMPLEXIS 2017

ISBN: (纸本)9789897582448

The proceedings contain 18 papers. The topics discussed include: security against collective attacks of a modified BB84 QKD protocol with information only in one basis;unikernels for cloud architectures: how single responsibility can reduce complexity, thus improving enterprise cloud security;parallelism strategies for neurophysiological delayed transfer entropy data processing - towards causal inference in big data;automatic tuning of a local search algorithm for estimating biological signals JPDs;a network of networks to reproduce the electrical features of an aptamer-ligand complex - what an electrical network tells about affinity;improvement of the detection of the QRS complex, T and P waves in an electrocardiogram signal using 12 leads versus 2 leads;a data-aware MultiWorkflow scheduler for clusters on WorkflowSim;real-world examples of agent based decision support systems for deep learning based on complex feed forward neural networks;probing complexity with epidemics: a new reactive immunization strategy;studying complex interactions in real time: an XMPP-based framework for behavioral experiments;Paramo and high-Andean simulation using reactive agents - hydrological role of high Andean ecosystems;analysis on the graph techniques for data-mining and visualization of heterogeneous biodiversity data sets;and data driven web experimentation on design and personalization.

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