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检索条件"机构=The key Laboratory of Embedded System and Service Computing"

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Improving bag-of-words representation with efficient twin feature integration 15

Improving bag-of-words representation with efficient twin fe...

引用

7th International Conference on Internet Multimedia computing and service, ICIMCS 2015

作者： Wang, Lei Wang, Hanli Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781450335287

In recent years, the Bag-of-Words (BoW) model has been widely used in most state-of-the-art large-scale image re-trieval systems. However, the standard BoW based systems suffer from low discriminative power of local features as well as quantization errors that significantly affect the retrieval performance. In this paper, twin feature is employed and well combined with two advanced techniques including Ham-ming Embedding (HE) and Multiple Assignment (MA) to construct a discriminative image retrieval system on BoW representation in an efficient way. Experimental results on two benchmark datasets Oxford5k and Paris6k demonstrate that the proposed technique can greatly refine the visual matching process and enhance the final performance for im-age retrieval. © 2015 ACM.

关键词： Image retrieval

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Behavioral authentication method for mobile gesture against resilient user posture 3

Behavioral authentication method for mobile gesture against ...

引用

2016 3rd International Conference on systems and Informatics, ICSAI 2016

作者： Liu, Qiang Wang, Mimi Zhao, Peihai Yan, Chungang Ding, Zhijun Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai China

ISBN: (纸本)9781509055210

The password pattern has become a widely used mobile authentication method. However, there are still some potential security problems since the passwords are easy to be cracked by some malicious software. An important research direction of improving its security is adding behavior pattern into the password pattern. The existing methods mainly used user's gesture behavior data such as the location, pressure and contact area of finger collected by touch screen to build a behavior authentication model, which did not consider the influence of user's posture on user's gesture behavior. This paper aims to propose a gesture authentication construction method that is resilient against the change of user's posture. Firstly, for the posture behavior data collected by mobile's orientation sensor and acceleration sensor, we use K-means algorithm to get user's postures. Secondly, we train a gesture authentication sub-model for each posture based on the data collected by touch screen. Finally, we give a behavior authentication method based on these models. Our experimental result shows that the method achieves an effect of 4.36% False Acceptance Rate (FAR) and 5.03% False Rejection Rate (FRR) © 2016 IEEE.

关键词： Authentication

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Discretized Gaussian Mixture Hyperprior for Learned Image Compression with Mask Module

Discretized Gaussian Mixture Hyperprior for Learned Image Co...

引用

2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Wang, Shengkai Wang, Hanli Tongji University Department of Computer Science and Technology Shanghai China Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Learned image compression approaches have shown great potential with promising results. However, according to the commonly used measurement methods, there still lies a performance gap between learned compression methods and the latest compression standard versatile video coding (VVC), because of the remaining redundancy existing in contemporary algorithms. To obtain a more accurate entropy model for rate estimation, discretized Gaussian mixture hyperprior is proposed in this work to parameterize the distribution of latent codes. In addition, a proposed mask module is exploited to enhance the feature extraction ability of the encoder and adaptively allocate bit rates. In this case, the proposed learned image compression model achieves the state-of-the-art performance among the existing learned compression methods and most compression standards on both Kodak24 and CLIC Mobile Validation datasets. The proposed model also outperforms VVC under several bitrate scenarios. © 2022 IEEE.

关键词： Image compression

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Low frequency analysis of resting-state fMRI

Low frequency analysis of resting-state fMRI

引用

2012 International Conference on Computer Science and Information Processing, CSIP 2012

作者： He, Lianghua Ji, Hongfei Wan, Meng Liu, Shuang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Center for Science and Technology Development of the Ministry Education Beijing China

ISBN: (纸本)9781467314114

Resting state functional magnetic resonance imaging (rsfMRI) is a relatively new and an powerful method for evaluating regional interactions that occur when a participant is not performing an explicit task. Because of sensitiveness to time delay and length of time courses, respectively, traditional methods of correlation and coherence based on region of interest are not very suitable for rsfMRI. In this paper, we analyzed low frequency property of rsfMRI data. Firstly, we calculated the low frequency of resting-state Blood-Oxygenation-Level-Dependent(BOLD) signal on every voxel using Welch method, based on which we analyzed the statistical distribution cross subjects and voxels. The low frequency feature is proved by a series of experiments to be more robust and consistent comparing with coorelation in time domain and coherency in frequency domain. We found that the property of low frequency statistical distribution is dominant on narrow band, which is around 0.0137HZ. © 2012 IEEE.

关键词： Frequency domain analysis

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DenseNet+inception and its application for electronic transaction fraud detection 21

DenseNet+inception and its application for electronic transa...

引用

21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and systems, HPCC/SmartCity/DSS 2019

作者： Chen, Zhuo Liu, Guanjun Department of Computer Science Key Laboratory of the Ministry of Education for Embedded System and Service Computing Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University Shanghai China

ISBN: (纸本)9781728120584

With the development of online payment, electronic transaction fraud events also take place often and result in huge financial losses. Recently, DenseNet as one of the most prominent Convolutional Neural Networks (CNNs) has achieved a remarkable success in many applications such as image recognition. However, when we apply DenseNet to the electronic transaction fraud detection in which the original data is directly as the input of DenseNet, a perfect performance cannot be obtained since the transaction data is different from the image data and the features of the original transaction data are not rich. The Inception module used in GoogLeNet (a kind of CNN) has different convolution kernels of different sizes and thus can enhance the feature mining ability. In this paper, we improve DenseNet (iDenseNet for short) in order to suit electronic transaction data and then propose two integration patterns of iDenseNet and Inception module. Experiments are done on two large datasets with millions of transaction records and compare our methods with CNN, DenseNet and Random Forest that are the state-of-the-art methods used in electronic transaction fraud detection. Results illustrate better performances of our methods. © 2019 IEEE.

关键词： Large dataset

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Design and implementation of communication module in passive ultrasonic sensor networks

Design and implementation of communication module in passive...

引用

2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010

作者： Han, Lina Zhao, Rui Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Third Research Institute of The Ministry of Public Security Shanghai China

ISBN: (纸本)9781424479566

Passive sensor networks can achieve accurate detection of target under complex environment. In order to adapt to different communication demands of sensor networks in different environments, this paper designed and implemented a wireless and wired mixed communication module, that is, a communication system combined short-distance wireless communication based on radio frequency technology with broadband cable communication. Simulation results show that our system can achieve the desired requirements in different circumstances. © 2010 IEEE.

关键词： Ultrasonic applications

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Application of SIRUS in credit card fraud detection 1

引用

7th International Conference on Computational Data and Social Networks, CSoNet 2018

作者： Zhang, Yuwei Liu, Guanjun Luan, Wenjing Yan, Chungang Jiang, Changjun Department of Computer Science and Technology Tongji University Shanghai201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China

ISBN: (数字)9783030046484

ISBN: (纸本)9783030046477

Credit card fraud problem is very common in recent years. It not only causes economic loss to people, but also causes trust crisis to enterprises. Due to the imbalance of data, fraud detection has always been tricky. In our previous work, we proposed a method of dealing with the class imbalance problem based on stacking ensemble learning and inverse random undersampling method (SIRUS). First, the inverse random undersampling method is used to generate multiple data subsets from the original data set. Then we use the stacking ensemble learning method for each data subset to train several different learners (also called first-level learners), and then the results generated by each first-level learner are taken as features to train a meta learner. We apply SIRUS to detect the credit card fraud in this paper. Our dataset comes from a financial company in China. A variety of measurements such as recall, precision, accuracy, F-measure, and G-mean to illustrate the effectiveness of our method in fraud detection. © Springer Nature Switzerland AG 2018.

关键词： Learning systems

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A fault prediction method based on modified Genetic Algorithm using BP neural network algorithm

A fault prediction method based on modified Genetic Algorith...

引用

2016 IEEE International Conference on systems, Man, and Cybernetics, SMC 2016

作者： Liu, Qing Feng, Zhang Liu, Min Shen, Weiming School of Electronic and Information Engineering Tongji University Shanghai201804 China Key Laboratory of Embedded System and Service Computing Tongji University Shanghai201804 China

ISBN: (纸本)9781509018970

In order to improve fault forecasting model accuracy of back propagation neural network (BPNN), an improved prediction method of optimized BPNN based on Multilevel Genetic Algorithm (MGA) was proposed. We design new chromosome with multilevel structure, improve the encoding mode, fitness function and genetic operator. Which can optimizes the initial values of weights, thresholds and the structure of BPNN synchronously. Enhancing the ability of nonlinear learning and generalization of BPNN. Case study of continuous casting equipment verified that the proposed model with higher prediction accuracy is better than classical BPNN and GA-BPNN prediction method for fault prediction. © 2016 IEEE.

关键词： Chromosomes

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Asymptotic signal bandwidth of impulse radio UWB communication networks

Asymptotic signal bandwidth of impulse radio UWB communicati...

引用

54th Annual IEEE Global Telecommunications Conference: "Energizing Global Communications", GLOBECOM 2011

作者： Xu, Juan College of Electronics and Information Engineering Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781424492688

The asymptotic signal bandwidth of various kinds of large-scale asynchronous Time Hopping Impulse Radio Ultra-Wide Band (TH-IR UWB) communication networks such that multiple access interference can be negligible with respect to output noise with high probability is derived. The asynchronous TH-IR UWB communication networks consist of n nodes distributed in a cube (three-dimension) or on a square (two-dimension) according to a Poisson point process. The theoretic results indicate that the obtained asymptotic bandwidth of IR-UWB signal is in proportion to the number of nodes, and that the asymptotic bandwidth of IR-UWB signal of dense network is much more than that of extended network. The results also reveal that the asymptotic bandwidth of three-dimensional network is less than that of two-dimensional network assuming that the number of nodes in the networks and the distance loss exponent are the same. As the bandwidth of IR-UWB signal satisfies the obtained theoretic bandwidth, the expression of probability of error of multi-node network is simplified to that of single node network. © 2011 IEEE.

关键词： Bandwidth

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Consensus in Second-Order Discrete-Time MAS With Distinct and Multiple Coupling Matrices 10

Consensus in Second-Order Discrete-Time MAS With Distinct an...

引用

10th International Conference on systems and Informatics, ICSAI 2024

作者： Sun, Chenggong Liu, Xiwei Tongji University Department of Computer Science and Technology Shanghai201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China

ISBN: (纸本)9798331510138

In this paper, we explore and establish several necessary and sufficient conditions that are instrumental in achieving consensus within second-order discrete-time multi-agent systems (SDMAS). Different with previous research, this study addresses the more intricate scenario where the velocity coupling matrix is distinct from the position coupling matrix. We introduce a novel eigenvector condition tailored to this challenge. Furthermore, in response to the burgeoning interest in multiweighted networks, this study is extended to SDMAS with multiple weights. We employ a technique, that rearranges the order of variables, to effectively simplify the analysis of multiweighted networks by transforming them into single-weighted equivalents. The efficacy of our method is substantiated through three numerical examples, which illustrate the practical value in elucidating consensus dynamics within SDMAS featuring diverse coupling matrices. © 2024 IEEE.

关键词： Multi agent systems

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