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3rd international conference on Information Management (ICIM)

作者： Wu, Husheng Yan, Qian Ling, Xiaodong Armed Police Force Engn Univ Mat Engn Coll Xian Shaanxi Peoples R China Satellite Maritime Tracking & Control Ctr Joint Lab Marine Measurement & Control Jiangying Peoples R China

ISBN: (纸本)9781509063062

The diesel engine, an efficient power machinery, is widely applied in many fields, such as vehicle, watercraft and petroleum machinery. The significance and difficulties of fault diagnosis on diesel engine is stated. Some domestic and foreign conventional methods of diesel state monitoring and fault diagnosis and their principles is discussed. Then, the applications of vibration signal time frequency analysis method and pattern recognition method in fault diagnosis for diesel engine are analyzed. What's more, the established fault diagnosis model which combined signal time frequency analysis method with pattern recognition method is discussed in detail. Finally, the development trend of marine diesel fault diagnosis technology is forecasted.

关键词： vibration signal processing diesel engine fault diagnosis pattern recognition

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3D Acquisition System for 3D Forms recognition 3

3D Acquisition System for 3D Forms Recognition

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3rd international conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Baibai, Kaoutar Elfakhouri, Naoufal Bellach, Benaissa Mohamed I Univ Sch Appl Sci Engeneering Lab LSE2I Oujda Morocco

ISBN: (纸本)9781538605516

This paper presents a new 3D information acquisition approach, which the aim is to reduce the amount of data to be processed in 3D shape recognition. This approach consists in extracting the 3D information from the deformations of the 2D lines projected on the 3D object, and transforms these deformations into a 1D signal. In order to simplify the extraction of descriptors of 3D shapes, the recognition process is consequently involved. In this framework, we developed a 3D acquisition system based on the projection of a multi-line pattern. We present in detail the different steps of the proposed approach, as well as the results obtained from each step. We describe the improvements we have made to 3D information acquisition processes.

关键词： multi-line 1D signal real time 2D-1D modelisation

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A Collaborative Tool for Modelling Multi-stage Attacks 3

A Collaborative Tool for Modelling Multi-stage Attacks

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3rd international conference on Information Systems Security and Privacy (ICISSP)

作者： Herwono, Ian El-Moussa, Fadi Ali BT Secur Futures Practice Res & Innovat Ipswich IP5 3RE Suffolk England

ISBN: (纸本)9789897582097

Cyber-attacks that are conducted in multiple stages over short or long periods of time are becoming more common. One approach for detecting such attacks at an early stage is to make use of attack patterns and attack signatures to provide a structure for correlating events collected from various sensors in the network. In this paper, we present our ongoing work on a pattern recognition system that aims to support cyber-defence analysts in sharing their attack knowledge and threat intelligence in the form of attack patterns or scenarios that can later be used to discover potential security breaches in their network. Our main goal is to allow the analysts to associate the attack patterns with their own organisation's security data and thus benefit from the collective attack knowledge without revealing any confidential information. We present the architecture of the system and describe a typical process for modelling multi-stage attacks. We demonstrate how its analytics engine interprets an attack pattern, tasks the data source agents to fetch and correlate relevant security events, and reports the results back for visualisation and further investigation.

关键词： Cyber Security Attack patterns pattern recognition System Knowledge Sharing

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pattern recognition of Cu(II), Pb(II), Hg(II), and Cd(II) in waste waters

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MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS 2017年第5期23卷 1141-1145页

作者： Popescu Mandoc, Luisa-Roxana Moldoveanu, Iuliana Stefan-van Staden, Raluca-Ioana Ungureanu, Eleonora Mihaela INCD ECOIND Bucharest Natl Res & Dev Inst Ind Ecol 71-73 Podu Dambovitei Rd Bucharest 060652 Romania Univ Politehn Bucuresti Fac Appl Chem & Mat Sci 1-7 Gh Polizu St Bucharest 011061 Romania Natl Inst Res Elect & Condensed Matter Lab Electrochem 202 Splaiul Independentei Str Bucharest 6 Romania Natl Inst Res Elect & Condensed Matter PATLAB 202 Splaiul Independentei Str Bucharest 6 Romania

pattern recognition of Cu(II), Pb(II), Hg(II) and Cd(II) in waste waters collected from a mining area, was performed using a fast screening method based on a new stochastic sensor. The stochastic sensor is based on physical immobilization of N,N'-ethylenebis[N-[(3-(pyrrole-1-yl)propyl) carbamoyl) methyl]-glycine]) in diamond paste. The limits of determination of the cations were as low as 10 pmol/L [for the assay of Cd(II)], and 100 pmol/L [for the assay of Cu(II), Hg(II), and Pb(II)]. The cations were determined from the waste water samples without any pretreatment of the water samples, within 20 min with recoveries higher than 98.80 %, and low RSD (%) values.

关键词： mining areas water samples Cations Screening Method Stochastic Waste Water Physical Restraint diamond paste pattern recognition

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A new GLBSIF Descriptor for Face recognition in the Uncontrolled Environments 3

A new GLBSIF Descriptor for Face Recognition in the Uncontro...

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3rd international conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Ameur, Bilel Belahcene, Mebarka Masmoudi, Sabeur Derbel, Amira Guidara Ben Hamida, Ahmed Sfax Univ Natl Engn Sch Sfax ENIS ATMS Adv Technol Med & Signals Soukra StKm 3-5BP 1173 Sfax 3038 Tunisia Mohamed Khider Univ Biskra Fac Sci & Technol LI3C BP 145 RP Biskra 07000 Algeria

ISBN: (纸本)9781538605516

In uncontrolled environments, the major challenges in face recognition, such as illumination variation, occlusion, facial expressions and poses, greatly affect the performance of Facial recognition Systems (FRS) especially those based on 2D information. We introduce, in this paper, a novel feature extraction approach named GLBSIF for face recognition in an uncontrolled environment. In our method, Gabor Wavelets (GW), Local Binary patterns (LBP) and Binarized Statistical Image Features (BSIF) were combined. Moreover, the dimension reduction was applied in order to minimize the pattern vectors using PCA. Finally, we used KNN-SRC for classification. The introduced technique was assessed on LFW database using several experiments and tested on other databases, such as PUBFIG83, FERET, *** B, ORL and IFD, in order to validate our approach. The best finding was provided when recognition Rate (RR) is equal to 97.81%.

关键词： Wavelets Gabor Local Descriptor Fusion Classification

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Tool condition monitoring using the chain code technique, pixel matching and morphological operations 3

Tool condition monitoring using the chain code technique, pi...

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3rd IEEE international conference on Computational Intelligence and Communication Technology (CICT)

作者： Sharma, Ekta Shivali Jyotsna Mahapatra, Prasant Doegar, Amit CSIR Cent Sci Instruments Org Biomed Instrumentat Div V-2Sect 30 Chandigarh 160030 India Natl Inst Tech Teachers Training & Res Dept Comp Sci & Engn Sect 26 Chandigarh 160019 India

ISBN: (纸本)9781509062188

Tool condition in various machining processes directly affects the quality of machined surfaces. Tool condition needs to be monitored with the purpose of evaluating the tool life and timely replacing it, if it is not in favourable condition. The present work focuses on monitoring of tool condition through image processing. The images of the single point lathe tool have been captured before and after machining by a machine vision system. These images are processed using MATLAB image processing toolbox software and tool condition has been evaluated. Different methods, i.e. Chain code, pixel matching and morphological operations have been successfully implemented for extracting the shape of the tool. Depending upon the shape of the tool, it has been classified as 'Normal' or 'Worn'.

关键词： Machine Vision System Digital Image Processing pattern recognition Chain code Chain Code Histogram (CCH) Pixel matching and Morphological operations

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Parallelization Of Digit recognition System Using Deep Convolutional Neural Network On CUDA 3

Parallelization Of Digit Recognition System Using Deep Convo...

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3rd IEEE international conference on Sensing, Signal Processing and Security (ICSSS)

作者： Singh, Srishti Paul, Amrit Arun, M. VIT Univ Sch Elect Engn Vellore Tamil Nadu India

ISBN: (纸本)9781509049295

A Compute Unified Device Architecture (CUDA) implementation of Deep Convolutional Neural Network (DCNN) for a digit recognition system is proposed to reduce the computation time of ANN and achieve high accuracy. A neural network with three layers of convolutions and two fully connected layers is developed by building input, hidden and output neurons to achieve an improved accuracy. The network is parallelized using a dedicated GPU on CUDA platform using Tensorflow library. A comparative analysis of accuracy and computation time is performed for sequential and parallel execution of the network on dual core (4 logical processors) CPU, octa core (16 logical processors) only CPU and octa core (16 logical processors) CPU with GPU systems. MNIST (Modified National Institute of Standards and Technology) and EMNIST (Extended MNIST) database are used for both training and testing. MNIST has 55000 training sets, 10000 testing sets and 5000 validation sets. EMNIST consists of 235000 training, 40000 testing and 5000 validation sets. The network designed requires high computation and hence parallelizing it shows significant improvement in execution time.

关键词： CUDA cuDNN Tensorflow GPU ANN CNN Back Propagation Supervised Learning Parallel Computing pattern recognition API

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Digital electric meter reading recognition based on horizontal and vertical binary pattern 3

Digital electric meter reading recognition based on horizont...

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3rd international conference on Electrical Information and Communication Technology, EICT 2017

作者： Anis, Atif Khaliluzzaman, Md. Yakub, Mohammad Chakraborty, Niloy Deb, Kaushik Dept. of Computer Science and Engineering International Islamic University Chittagong Chittagong4318 Bangladesh Dept. of Computer Science and Engineering Chittagong University of Engineering and Technology Chittagong4349 Bangladesh

ISBN: (纸本)9781538623053

Digital meter reading recognition from a digital electric meter image is the key step in the field of digital image processing to evaluate the meter readings from different environmental conditions automatically. This work has gain important for the purpose of automatic generation of electric bill from digital electric meter image. In this regard, a digital electric meter reading recognition framework is proposed in this paper. For that initially, the input image is normalized and converted to YCbCr image. As the digital electric meter reading region is resolute with color light, especially green, the reading region is extracted from YCbCr image based on the value of the Cb and Cr. After that, Canny edge operator is employed on the extracted region to find the edge image. In this edge image, the individual digit's edge gaps are filled up through the morphological operation to find individually connected digit edge image. These individual digits are segmented from an edge image through the vertical projection. Furthermore, the individually segmented digits are filled and thinned to detect the shapes of the digits. From these segmented digit shapes the Horizontal and Vertical Binary (HVB) pattern features are extracted. This is the key contribution of this paper. Finally, based on the HVB patterns the digital meter reading sequence is recognized. The experimental result reveals that the proposed framework is practical and effective. © 2017 IEEE.

关键词： Image processing

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Computer-aided diagnosis system for ulcer detection in wireless capsule endoscopy videos 3

Computer-aided diagnosis system for ulcer detection in wirel...

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3rd international conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017

作者： Charfi, Said Ansari, Mohamed El LabSIV Department of Computer Science Faculty of Sciences Ibn Zohr University BP 8106 Agadir80000 Morocco

ISBN: (纸本)9781538605516

In this paper, we present a new feature descriptor for automatic recognition of frames with ulcer in Wireless Capsule Endoscopy (WCE) images. The new approach is based on the fact that the ulcer disease exhibits various features that can not be detected with a single descriptor. Hence, we have combined two stages of the art descriptors in order to get more powerful one. Complete Local Binary pattern (CLBP) descriptor is used to detect the texture information in the image. In parallel, the Global Local Oriented Edge Magnitude pattern (Global LOEMP) descriptor is employed to extract the color features. Finally, we combine the feature vectors to get a more discriminating one. Experiments were conducted and the results are satisfactory. © 2017 IEEE.

关键词： Local binary pattern

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Facial Based Attendance Monitoring System Using Discriminative Robust Local Binary pattern

Facial Based Attendance Monitoring System Using Discriminati...

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3rd international conference on Computing, Communication, Control and Automation (ICCUBEA)

作者： Tamboli, Nilofer Sardeshmukh, M. M. Sinhgad Acad Engn Elect & Telecommun Pune Maharashtra India

ISBN: (纸本)9781538640081

In this research we have proposed Students attendance marking system using face recognition for high efficient signal transfer system applications .Face detection is an important role in many applications. Face detection overlapping is one of the important works in face detecting applications. In this paper DRLBP algorithm is used to identify overlapped faces detection. Initially the face is detected from database images using DRLBP feature extraction. This feature extraction result is compared to our test images. Finally classified method is used where we can classify and get the attendance validation result.

关键词： Facial recognition Facial Identification Attendance Management Attendance Validation

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