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An All-Optical Binary pattern recognition System Applied in Photonic Firewall based on VPI Simulation 24

An All-Optical Binary Pattern Recognition System Applied in ...

引用

24th OptoElectronics and Communications conference (OECC) / international conference on Photonics in Switching and computing (PSC)

作者： Guo, Junfeng Li, Xin Tang, Ying Zhang, Lu Gao, Tao Huang, Shanguo Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing Peoples R China

An all-optical binary pattern recognition system based on XOR is simulated by VPI for the first time. The simulation results show the system can recognize and locate target in the data at 10Gb/s and 40Gb/s.

ISBN: (纸本)9784885523212

关键词： Semiconductor optical amplifiers optical signal processing

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pattern of Diffusion recognition in a Molecular Communication Model 1st

Pattern of Diffusion Recognition in a Molecular Communicatio...

引用

1st international conference on Applied computing Research to Support Industry: Innovation and Technology, ACRIT 2019

作者： Jani, Athraa Juhi Department of Computer Science Al-Mustansiriyah University Baghdad Iraq

ISBN: (纸本)9783030387518

A nanomachine is the basic functional unit in nanotechnology that can perform simple tasks, like sensing and actuation. A set of nanomachines can perform more complex tasks through communicating and sharing information, and by that, they form a nanonetwork. Different communication techniques are proposed for information exchange among nanomachines. Molecular communication is one of these techniques, which is a bio-inspired communication mechanism. In this paper a time slotted model consist of n nanomachines in a bounded environment is considered. These nanomachines are communicate according to diffusion based molecular communication. Information molecules are encoded based on the variation in the concentration of molecules in the communication medium. Thus, the receiver nanomachine decode the sensed information molecules during a certain time slot as ‘1’, if its concentration exceeds a certain threshold τ, and ‘0’ otherwise. The main objective is to study the performance of diffusion based molecular communication model, the pattern of diffusion was explored, by inspecting how a receiver nanomachine could distinguish a message from one transmitter nanomachine at a distance d or two transmitter nanomachines at different distances. The information molecules were represented as 2-bits by using 22 different values with 22 − 1 thresholds. In the implemented experiments the effects of distance, time, sensed molecular concentration and interference are considered. © 2020, Springer Nature Switzerland AG.

关键词： Diffusion

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2nd international conference on Computational Intelligence, Security and Internet of Things, ICCISIoT 2019

2nd International Conference on Computational Intelligence, ...

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2nd international conference on Computational Intelligence, Security and Internet of Things, ICCISIoT 2019

ISBN: (纸本)9789811536656

The proceedings contain 37 papers. The special focus in this conference is on Computational Intelligence, Security and Internet of Things. The topics include: Machine learning based efficient multi-copy routing for OppIoT networks;An open-hardware approach for IoT enabled smart meter monitoring and controlling system using MQTT protocol;Performance of NOMA-MUSA system for 5G Using m-ZCZ sequences;ioT based multi-sensor data acquisition system for the application of smart agriculture;context-oriented user-centric search system for the IoT based on fuzzy clustering;implementation of a smart embedded system for passenger vessel safety;routine statistical framework to speculate kannada lip reading;empirical analysis on the effect of image compression and denoising using different wavelets on iris recognition;segmentation of chart images using H-Means algorithm;hand vein biometric recognition using local binary pattern;distance calculation of an object in a stereo vision system;comparative assessment of consumer perception on sports brands using data mined from online communities;analytical modelling of internet of vehicles (IoV) by IoT cloud for dipping traffic congestion and safety alert: A review;Object detection using point feature matching based on SURF algorithm;diabetes mellitus prediction using ensemble machine learning techniques;incepting on language structures with phonological and corpus analysis using multilingual computing;morphotactics of manipuri verbs: A finite state approach;proportional analysis of feature extraction for tamil handwritten characters using centroid based method;mobile supported interaction modeling to find engagement of acolyte in live classroom;Integration of BYOD technology in traditional classroom: A statistical approach;preface;real time adaptive street lighting system.

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Combination filter for keypoint detection and pattern recognition in traffic visual surveillance 2

Combination filter for keypoint detection and pattern recogn...

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2nd international conference on Intelligent computing, Instrumentation and Control Technologies, ICICICT 2019

作者： Snehalatha, O.J. Sureshkumar, E. Govt. Rajiv Gandhi Institute of Technology Dept. of ECE Kottayam India College of Engineering Dept. of ECE Trivandrum India

ISBN: (纸本)9781728102832

The detection of keypoints is very important for several computer applications. There are several ways for keypoint detection and pattern recognition. Earliest work proposes a trainable filter called COSFIRE filter which is a combination of bank of log gabor filters. This proposesd work interested in configuration of more sophisticated combination filter using bank of log gabor filters with bigger support. The specific function that use here to combine filter response is weighted geometric mean, essentially multiplication, which has specific advantages regarding shape recognition and robustness to contrast variations. The proposed work tends to demonstrate the effectiveness of filter in traffic visual surveillance including detection and recognition of traffic signs in complicated scenes. © 2019 IEEE.

关键词： pattern recognition

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Dimension Reduction for Efficient pattern recognition in High Spatial Resolution Data Using Quantum Algorithms 32

Dimension Reduction for Efficient Pattern Recognition in Hig...

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32nd IEEE international System-on-Chip conference (IEEE SOCC)

作者： Mahmud, Naveed El-Araby, Esam Univ Kansas Elect Engn & Comp Sci Lawrence KS 66045 USA

ISBN: (纸本)9781728134826

With the promising advancement in quantum computing technology in the last decade, there is a strong motivation to find suitable applications for quantum algorithms and quantum computers. Domains such as High Energy Physics (IIEP) have an enormous readout count of high-resolution data. Performing pattern recognition on this readout is computationally. , challenging and time-consuming because of the multi-dimensionality of the data. In this paper, we propose a methodology that employs quantum algorithms such as Quantum Wavelet Transform and Grover's search algorithm for time-efficient pattern recognition in data sets that are characterized by high spatial resolution and high dimensionality. The motivation behind using quantum algorithms is the potential speedup relative to classical methods, when performed by a quantum computer. In our proposed methodology, Quantum Wavelet Transform is performed on the high spatial resolution data to reduce its dimensionality while quantum Grover's search algorithm is employed to search for target patterns in the reduced data set. Performing the search operation on data with reduced spatial resolution, minimizes processing overheads and computation times. Moreover, use of quantum techniques yield faster results, compared to classical dimension reduction and search methods. We demonstrate the feasibility of the proposed methodology by emulating the quantum algorithms on classical hardware based on field programmable gate arrays (FPGAs). A high performance reconfigurable computer (IIPRC) was used for the experimental evaluation. The obtained results are favorable towards our proposed approach.

关键词： Quantum computing Quantum Emulation

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An efficient technique for facial expression recognition using multistage hidden markov model 2nd

An efficient technique for facial expression recognition usi...

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2nd international conference of the series soft computing: Theories and Applications, SoCTA 2017

作者： Rahul, Mayur Mamoria, Pushpa Kohli, Narendra Agrawal, Rashi AKTU Lucknow India Department of Computer Applications UIET CSJMU Kanpur India Department of Computer Science & Engineering HBTU Kanpur India Department of IT UIET CSJMU Kanpur India

ISBN: (纸本)9789811305887

Partition-based feature extraction is widely used in the pattern recognition and computer vision. This method is robust to some changes like occlusion, background, etc. In this paper, partition-based technique is used for feature extraction and extension of HMM is used as a classifier. The new introduced multistage HMM consists of two layers. In which bottom layer represents the atomic expression made by eyes, nose, and lips. Further upper layer represents the combination of these atomic expressions such as smile, fear, etc. Six basic facial expressions are recognized, i.e., anger, disgust, fear, joy, sadness, and surprise. Experimental result shows that proposed system performs better than normal HMM and has the overall accuracy of 85% using JAFFE database. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Local binary pattern

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Research on Fire Detection and Image Information Processing System Based on Image Processing

Research on Fire Detection and Image Information Processing ...

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Advance in Ambient computing and Intelligence (ICAACI), international conference on

作者： Wentao Xiong Songzi Fire Rescue Brigade Jingzhou Songzi Hubei China

ISBN: (数字)9781728197531

ISBN: (纸本)9781728197548

In this paper, based on digital image processing technology, a series of preprocessing operations such as graying based on color components, filtering denoising, histogram equalization and so on are carried out to enhance the image effect. Then, the suspicious fire area obtained based on color component difference image is processed by threshold segmentation and edge detection. In the processing of flame image, pattern recognition technology is of great significance to the extraction of flame image. Computer vision theory is the key to fire location. With this scheme, the system can effectively eliminate the interference of distance and light intensity in fire detection, and improve the recognition accuracy.

关键词： Image segmentation Digital images Image edge detection Fires Information processing pattern recognition Monitoring

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Hybrid Model of Vehicle recognition Based on Convolutional Neural Network

Hybrid Model of Vehicle Recognition Based on Convolutional N...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Chan Su Jianguo Wei School of software Nanchang University Nanchang China

ISBN: (纸本)9781728176499;9781728176505

With the improvement of people's living standard, the number of cars on the road has increased dramatically. Vehicle recognition is greatly significant for intelligent traffic management. In this paper, a hybrid model of vehicle recognition algorithm based on VGG16-softmax hybrid model is proposed. The convolutional neural network called VGG16 is used, Imagenet is used for pre-training, migration learning is used to migrate parameters to the new training model, variational auto-encoder is used for data reconstruction, and finally softmax multi-classifier is used for classification. Experiments show that this method can save time, get better vehicle feature of details and higher accuracy.

关键词： Training Uncertainty Transfer learning Training data Feature extraction Data models pattern recognition

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Control Chart pattern recognition Based on Convolution Neural Network

Control Chart Pattern Recognition Based on Convolution Neura...

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international conference on Smart Innovations in Communications and Computational Sciences (ICSICCS)

作者： Miao, Zhihong Yang, Mingshun Xian Univ Technol Sch Mech & Precis Instrument Engn Xian 710048 Shaanxi Peoples R China

ISBN: (纸本)9789811089718;9789811089701

Quality control chart pattern recognition plays an extremely important role in controlling the products quality. By means of real-time monitoring control, the abnormal status of the product during production can be timely observed. A method of control pattern recognition based on convolution neural network is proposed. Firstly, the control chart patterns (CCPs) are analyzed, the statistical characteristics and shape features of the control charts are considered, and the appropriate characteristics to distinguish the different abnormal patterns are selected;secondly, deep learning convolution neural network is trained and learned;finally, the feasibility and effectiveness of the control chart pattern recognition are verified through Monte Carlo simulation.

关键词： Quality control chart pattern recognition Convolution neural Network Monte Carlo Deep learning

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Classification of Aviation Safety Reports using Machine Learning

Classification of Aviation Safety Reports using Machine Lear...

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international conference on Artificial Intelligence and Data Analytics for Air Transportation (AIDA-AT)

作者： Vincent de Vries Aerospace Operations Safety Institute Royal Dutch Aerospace Centre Amsterdam Netherlands

The following topics are dealt with: airports; air traffic control; aircraft; aerospace computing; learning (artificial intelligence); transportation; decision making; data handling; air safety; image processing.

ISBN: (数字)9781728153803

ISBN: (纸本)9781728153810

关键词： aerospace computing aerospace safety aircraft pattern classification random forests text analysis aerospace safety aerospace computing text processing pattern recognition Aircraft Taxonomy aviation security aerospace industry Artificial Intelligence Machine Learning

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