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Scalable apriori-based frequent pattern discovery

Scalable apriori-based frequent pattern discovery

引用

2009 international conference on Computational Science and Engineering, CSE '09

作者： Chester, Sean Sandler, Ian thomo, Alex University of Victoria Victoria MN Canada

ISBN: (纸本)9780769538235

Frequent pattern discovery, the task of finding sets of items that frequently occur together in a dataset, has been at the core of the field of data mining for the past sixteen years. In that time, the size of datasets has grown much faster than has the ability of existing algorithms to handle those datasets. Consequently, improvements are needed. In this paper we take the classic algorithm for the problem, A Priori, and by adding a vertical sort drastically improve its performance characteristics when processing very large data sets. We use the benchmark large dataset webdocs from the FIMI 2004 conference to contrast our performance against several state-of-the-art implementations and demonstrate both equal efficiency with lower memory usage at all support thresholds and also the ability to mine support thresholds as yet unattempted in literature. We also indicate how this work can be extended to achieve yet more impressive results.

关键词： Data mining

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Locating facial features using SOFM

Locating facial features using SOFM

引用

international conference on pattern recognition

作者： B. Takacs H. Wechsler Institute for Computational Sciences George Mason University Fairfax VA USA Department of Computer Science George Mason University Fairfax VA USA

We describe a novel and general approach for the detection of facial features such as the eyes. the approach is based on biologically motivated processing and classification schemes. the processing involves retinal sampling along P-type lattices and micro saccades, while classification is done using the self-organizing feature map (SOFM). the optimal set of eye templates is found by an enhanced SOFM approach using cross-validation training. Experimental results are presented to prove the feasibility of our approach.

关键词： Facial features Face detection Face recognition Humans pattern recognition Feature extraction Principal component analysis Biology computing Eyes Retina

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computing depth from out-of-focus blur using a local frequency representation

Computing depth from out-of-focus blur using a local frequen...

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international conference on pattern recognition

作者： M. Gokstorp Image Processing Laboratory Computer Engineering Division Department of Electrical Engineering Linkoping University Sweden

We present a method to compute depth from the amount of defocus in two images obtained from the same view-point but with different camera parameter settings. the change in defocus (blur) between the two images is proportional to the depth in the scene. We introduce a novel method to estimate the blur using a multiresolution local frequency representation of the input image pair. A confidence measure is used to discriminate between high error and low error blur estimates. Quantitative experimental results are shown for both real and synthetic images.

关键词： Layout Cameras Frequency estimation Robustness Lenses Focusing Optical imaging Geometry Image processing Laboratories

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Performance evaluation of texture measures with classification based on Kullback discrimination of distributions

Performance evaluation of texture measures with classificati...

引用

international conference on pattern recognition

作者： T. Ojala M. Pietikainen D. Harwood Department of Electrical Engineering University of Oulu Oulu Finland Oulun Yliopisto Oulu FI Center for Automation Research University of Maryland College Park MD USA

this paper evaluates the performance both of some texture measures which have been successfully used in various applications and of some new promising approaches. For classification a method based on Kullback discrimination of sample and prototype distributions is used. the classification results for single features with one-dimensional feature value distributions and for pairs of complementary features with two-dimensional distributions are presented.

关键词： Rotation measurement Image texture analysis Prototypes Histograms Autocorrelation Distributed computing Electric variables measurement Analysis of variance Performance evaluation Automation

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Advances in Artificial Intelligence and Its Applications 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Félix Castro Alexander Gelbukh Miguel González

ISBN: (数字)9783642451140

ISBN: (纸本)9783642451133

the two-volume set LNAI 8265 and LNAI 8266 constitutes the proceedings of the 12th Mexican international conference on Artificial Intelligence, MICAI 2013, held in Mexico City, Mexico, in November 2013. the total of 85 papers presented in these proceedings were carefully reviewed and selected from 284 submissions. the first volume deals with advances in artificial intelligence and its applications and is structured in the following five sections: logic and reasoning; knowledge-based systems and multi-agent systems; natural language processing; machine translation; and bioinformatics and medical applications. the second volume deals with advances in soft computing and its applications and is structured in the following eight sections: evolutionary and nature-inspired metaheuristic algorithms; neural networks and hybrid intelligent systems; fuzzy systems; machine learning and pattern recognition; data mining; computer vision and image processing; robotics, planning and scheduling and emotion detection, sentiment analysis and opinion mining.

关键词： Artificial Intelligence Computer Imaging, Vision, pattern recognition and Graphics Health Informatics Information Systems Applications (incl. Internet) Information Storage and Retrieval Algorithm Analysis and Problem Complexity

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Protection of User Sensitive Information Based on SIR Model 12

Protection of User Sensitive Information Based on SIR Model

引用

12th international conference on Advanced Cloud and Big Data, CBD 2024

作者： Wang, Hai Ji, Shuo Hao, Mingyuan Xu, Guodong School of Information Science and Technology Northwest University Xi'an710127 China

ISBN: (纸本)9798331511074

In the mobile CDN environment, the information spread within the coverage of any edge server may contain sensitive information, so the sensitive information needs to be protected during the propagation process. this paper proposes to use today's more mature natural language processing (NLP) technology on the edge server. If it is detected that the information contains sensitive information through the device connection and data transmission in the coverage of an edge server, the propagation of the information will be limited according to the classification of infectious diseases. In this paper, we first assume that the sensitive information is released in the network environment, and then use SIR model to simulate the information dissemination situation. We simulate the sensitive information dissemination situation in two different situations: the edge server restricts the information dissemination and the edge server does not restrict the information dissemination, and compare the experimental results of the two different situations. In this paper, dolphin network data set and simulation data set are used for experimental verification. the experimental results show that, compared with the traditional cloud computing framework, this method can effectively inhibit the spread of sensitive information in the mobile CDN network framework and limit the spread of sensitive information. © 2024 IEEE.

关键词： Mobile edge computing

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3D Adaptive Beamforming Approach with a Fine-Tuned Deep Neural Network 12

3D Adaptive Beamforming Approach with a Fine-Tuned Deep Neur...

引用

12th international conference on Modern Circuits and Systems Technologies, MOCAST 2023

作者： Mallioras, Ioannis Yioultsis, Traianos V. Kantartzis, Nikolaos V. Lazaridis, Pavlos I. Zaharis, Zaharias D. Aristotle University of Thessaloniki School of Electrical and Computer Eng. Thessaloniki Greece Maggioli SpA Santarcangelo Di Romagna Italy University of Huddersfield School of Computing and Eng. Huddersfield United Kingdom

ISBN: (纸本)9798350321074

Adaptive beamforming is an essential smart antenna operation, with increasing importance for beyond 5G networks. However, the increased computational complexity of deterministic beamforming algorithms highlights their inability to respond to future demands. In this paper we approach the problem of mapping the angles of arrival of incoming signals on an 8x8 uniform planar array, to a desired complex feeding weight vector. We investigate a well-known deep learning model, the multi-layer perceptron, and we train it on a large dataset produced by the null-steering beamforming (NSB) algorithm. In order to propose the most efficient design, we fine tune the hyperparameters and each individual layer of the deep feedforward neural network architecture. the proposed model is able to reach excellent beam-steering accuracy, with signal to interference-plus-noise ratio levels similar to that of NSB, at a significantly lower response time. Finally, we provide a statistical analysis to compare the performance of each beamformer. © 2023 IEEE.

关键词： Signal to noise ratio

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Digital Human Modeling 1

引用

丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783540733218

ISBN: (纸本)9783540733188

the 12th international conference on Human-Computer Interaction, HCI Inter- tional 2007, was held in Beijing, P.R. China, 22-27 July 2007, jointly with the Symposium on Human Interface (Japan) 2007, the 7th international conference on Engineering Psychology and Cognitive Ergonomics, the 4th international conference on Universal Access in Human-Computer Interaction, the 2nd international Conf- ence on Virtual Reality, the 2nd international conference on Usability and Inter- tionalization, the 2nd international conference on Online Communities and Social computing, the 3rd international conference on Augmented Cognition, and the 1st international conference on Digital Human Modeling. A total of 3403 individuals from academia, research institutes, industry and g- ernmental agencies from 76 countries submitted contributions, and 1681 papers, judged to be of high scientific quality, were included in the program. these papers address the latest research and development efforts and highlightthe human aspects of design and use of computing systems. the papers accepted for presentation th- oughly cover the entire field of Human-Computer Interaction, addressing major - vances in knowledge and effective use of computers in a variety of application areas. this volume, edited by Vincent G. Duffy, contains papers in the thematic area of Digital Human Modeling, addressing the following major topics: • Shape and Movement Modeling and Anthropometry • Building and Applying Virtual Humans • Medical and Rehabilitation Applications • Industrial and Ergonomic Applications

关键词： User Interfaces and Human Computer Interaction Simulation and Modeling Image Processing and Computer Vision pattern recognition Artificial Intelligence Information Systems Applications (incl. Internet)

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Solomonoff coding as a means of introducing prior information in syntactic pattern recognition

Solomonoff coding as a means of introducing prior informatio...

引用

international conference on pattern recognition

作者： A.L.N. Fred J.M.N. Leitao Instituto de Telecomunicações Department Engineering Electrotécnica e de Computadores Instituto Superior Technico Lisboa Portugal

In this paper, a solution to the problem of introducing a priori information in phrase structured syntactic pattern recognition systems is proposed. the method consists of devising subpatterns (representing regularities in the symbol sequences) by means of Solomonoff coding, and using these subpatterns as a priori information for constraining the production of structural samples, which serve as input to grammar inference algorithms. We have shown, in a previous work, the adequacy of syntactic modeling in automatic sleep analysis. In this paper, a further improvement is achieved by applying the proposed methodology.

关键词： pattern recognition Information theory Stochastic processes Entropy Computational complexity Turing machines Telecommunication computing Production Artificial intelligence Learning systems

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An Aircraft Identification System Using Convolution Neural Networks 12

An Aircraft Identification System Using Convolution Neural N...

引用

12th IEEE international conference on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications, IDAACS 2023

作者： Turchenko, Viktor Turchenko, Iryna Vasylkiv, Nadiia West Ukrainian National University Department for Information Computer Systems and Control Ternopil46000 Ukraine McMaster University Department of Computing and Software HamiltonL8S 4L8 Canada Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine

ISBN: (纸本)9798350358056

the task of aircraft identification using their registration number is important as visual identification remains the only method of their identification in case of air traffic control systems or radar failure. In this paper, an analysis of known solutions was carried out and an aircraft identification system was developed using a pre-trained YOLO (You Only Look Once) deep convolutional neural network and Optical Character recognition (OCR) technology. the system consists of three modules: the M1 module is designed for the detection of region of interest-tail, the M2 module is designed for the detection of region of interest-registration number, the M3 module is designed for the classification of the registration number. 2309 aircraft images were used for training, 426 for validation and 408 for testing from the Fine-Grained Visual Classification of Aircraft (FGVC-Aircraft) dataset. Our results show that the mean average precision for the M1 and M2 YOLOv7 models on the test set were 0.92 and 0.85 respectively, and for the module M3 OCR technology the classification error was 0.2. © 2023 IEEE.

关键词： aircraft convolutional neural networks deep learning detection transfer learning YOLOv7

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