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Artificial Intelligence and Soft computing 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Leszek Rutkowski Marcin Korytkowski Rafał Scherer Ryszard Tadeusiewicz Lotfi A. Zadeh Jacek M. Zurada

ISBN: (数字)9783642386107

ISBN: (纸本)9783642386091

the two-volume set LNAI 7894 and LNCS 7895 constitutes the refereed proceedings of the 12th international conference on Artificial Intelligence and Soft computing, ICAISC 2013, held in Zakopane, Poland in June 2013. the 112 revised full papers presented together with one invited paper were carefully reviewed and selected from 274 submissions. the 56 papers included in the second volume are organized in the following topical sections: evolutionary algorithms and their applications; data mining; bioinformatics and medical applications; agent systems, robotics and control; artificial intelligence in modeling and simulation; and various problems of artificial intelligence.

关键词： Artificial Intelligence Information Systems Applications (incl. Internet) Computation by Abstract Devices Database Management Information Storage and Retrieval Computer Imaging, Vision, pattern recognition and Graphics

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Computer Vision - ACCV 2014 Workshops 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： C. V. Jawahar Shiguang Shan

ISBN: (数字)9783319166346

ISBN: (纸本)9783319166339

the three-volume set, consisting of LNCS 9008, 9009, and 9010, contains carefully reviewed and selected papers presented at 15 workshops held in conjunction with the 12th Asian conference on Computer Vision, ACCV 2014, in Singapore, in November 2014. the 153 full papers presented were selected from numerous submissions. LNCS 9008 contains the papers selected for the Workshop on Human Gait and Action Analysis in the Wild, the Second international Workshop on Big Data in 3D Computer Vision, the Workshop on Deep Learning on Visual Data, the Workshop on Scene Understanding for Autonomous Systems, and the Workshop on Robust Local Descriptors for Computer Vision. LNCS 9009 contains the papers selected for the Workshop on Emerging Topics on Image Restoration and Enhancement, the First international Workshop on Robust Reading, the Second Workshop on User-Centred Computer Vision, the international Workshop on Video Segmentation in Computer Vision, the Workshop: My Car Has Eyes: Intelligent Vehicle with Vision Technology, the third Workshop on E-Heritage, and the Workshop on Computer Vision for Affective computing. LNCS 9010 contains the papers selected for the Workshop on Feature and Similarity for Computer Vision, the third international Workshop on Intelligent Mobile and Egocentric Vision, and the Workshop on Human Identification for Surveillance.

关键词： Computer Imaging, Vision, pattern recognition and Graphics User Interfaces and Human Computer Interaction Media Design Geometry

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Computer Vision - ACCV 2014 Workshops 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： C.V. Jawahar Shiguang Shan

ISBN: (数字)9783319166315

ISBN: (纸本)9783319166308

关键词： Computer Imaging, Vision, pattern recognition and Graphics User Interfaces and Human Computer Interaction Media Design Geometry

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Local Trinary patterns for human action recognition

Local Trinary Patterns for human action recognition

引用

international conference on Computer Vision (ICCV)

作者： Lahav Yeffet Lior Wolf Blavatnik School of Computer Science Tel-Aviv University Israel

We present a novel action recognition method which is based on combining the effective description properties of Local Binary patterns with the appearance invariance and adaptability of patch matching based methods. the resulting method is extremely efficient, and thus is suitable for real-time uses of simultaneous recovery of human action of several lengths and starting points. Tested on all publicity available datasets in the literature known to us, our system repeatedly achieves state of the art performance. Lastly, we present a new benchmark that focuses on uncut motion recognition in broadcast sports video.

关键词： Humans pattern recognition Histograms Optical computing Atom optics Concatenated codes Computer science pattern matching System testing Benchmark testing

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Advanced computing 1

引用

丛书名： Communications in Computer and Information Science

1000年

作者： Deepak Garg V. A. Narayana Vijaya Kumar Koppula P. N. Suganthan Jaume Anguera Suneet Kumar Gupta

ISBN: (数字)9783031356445

ISBN: (纸本)9783031356438

this two-volume set constitutes reviewed and selected papers from the 12th international Advanced computing conference, IACC 2022, held in Hyderabad, India, in December 2022.;the 72 full papers and 6 short papers presented in the volume were thorougly reviewed and selected from 415 submissions. the papers are organized in the following topical sections: AI in industrial applications; application of AI for disease classification and trend analysis; design of agricultural applications using AI; disease classification using CNN; innovations in AI; system security and communication using AI; use of AI in human psychology; use of AI in music and video industries.

关键词： Artificial Intelligence Computer Systems Organization and Communication Networks Computer Applications Computers and Education Computer Imaging, Vision, pattern recognition and Graphics

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Fixed-lag particle filter for continuous context discovery using Indian Buffet Process

Fixed-lag particle filter for continuous context discovery u...

引用

2014 12th IEEE international conference on Pervasive computing and Communications, PerCom 2014

作者： Nguyen, thuong Gupta, Sunil Venkatesh, Svetha Phung, Dinh Centre for Pattern Recognition and Data Analytics Deakin University Australia

ISBN: (纸本)9781479934454

Exploiting context from stream data in pervasive environments remains a challenge. We aim to extract proximal context from Bluetooth stream data, using an incremental, Bayesian nonparametric framework that estimates the number of contexts automatically. Unlike current approaches that can only provide final proximal grouping, our method provides proximal grouping and membership of users over time. Additionally, it provides an efficient online inference. We construct co-location matrix over time using Bluetooth data. A Poisson-exponential model is used to factorize this matrix into a factor matrix, interpreted as proximal groups, and a coefficient matrix that indicates factor usage. the coefficient matrix follows the Indian Buffet Process prior, which estimates the number of factors automatically. the non-negativity and sparsity of factors are enforced by using the exponential distribution to generate the factors. We propose a fixed-lag particle filter algorithm to process data incrementally. We compare the incremental inference (particle filter) with full batch inference (Gibbs sampling) in terms of normalized factorization error and execution time. the normalized error obtained through our incremental inference is comparable to that of full batch inference, whilst the execution time is more than 100 times faster. the discovered factors have similar meaning to the results of the popular Louvain method for community detection. © 2014 IEEE.

关键词： Bluetooth

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Fast Retrieval Method of English Translation Corpus Based on Top-k Query Algorithm 12th

Fast Retrieval Method of English Translation Corpus Based on...

引用

12th international conference on Frontier computing, FC 2022

作者： Qin, Lihui International Business Department Dongfang College Shandong University of Finance and Economics Shandong Taian271000 China

ISBN: (纸本)9789819914272

the fast retrieval method of English translation corpus based on Top-k query algorithm is a technology to retrieve the most commonly used words in English translation corpus. the top k query algorithm uses the first k most commonly used words to retrieve all other words in the text, and then returns them to the user. this technique uses it to find out which word in the Chinese translation corpus is more commonly used than other words. the fast retrieval method of English translation corpus is a kind of machine translation, which uses statistical technology to obtain high-quality results at low computational cost. It is the most commonly used method to translate text into another language, and is widely used in many applications, such as automatic speech recognition (ASR) system, web search engine and so on. Compared with other methods, the main advantage of this technology is that it can process very large data sets without significant quality loss. Since then, this method has been widely used and studied by many researchers in various fields such as computer science, linguistics, information retrieval and natural language processing. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Information retrieval

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pattern recognition Techniques in Image-Based Material Classification of Ancient Manuscripts 12th

Pattern Recognition Techniques in Image-Based Material Class...

引用

12th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Dhali, Maruf A. Reynolds, thomas Alizadeh, Aylar Ziad Nijdam, Stephan H. Schomaker, Lambert Univ Groningen Dept Artificial Intelligence Groningen Netherlands Royal Holloway Univ London Dept Comp Sci London England

ISBN: (纸本)9783031547256;9783031547263

Classifying ancient manuscripts based on their writing surfaces often becomes essential for palaeographic research, including writer identification, manuscript localization, date estimation, and, occasionally, forgery detection. Researchers continually perform corroborative tests to classify manuscripts based on physical materials. However, these tests, often performed on-site, require actual access to the manuscript objects. these procedures involve specific expertise in manuscript handling, a considerable amount of time, and cost. Additionally, any physical inspection can accidentally damage ancient manuscripts that already suffer degradation due to aging, natural corrosion, and damaging chemical treatments. Developing a technique to classify such documents using noninvasive techniques with only digital images can be extremely valuable and efficient. this study uses images from a famous historical collection, the Dead Sea Scrolls, to propose a novel method to classify the materials of the manuscripts. the proposed classifier uses the two-dimensional Fourier transform to identify patterns within the manuscript surfaces. Combining a binary classification system employing the transform with a majority voting process is adequate for this classification task. this initial study shows a classification percentage of up to 97% for a confined amount of manuscripts produced from either parchment or papyrus material. In the extended work, this study proposes a hierarchical k-means clustering method to group image fragments that are highly likely to originate from a similar source using color and texture features calculated on the image patches, achieving 77% and 68% for color and texture clustering with 100% accuracy on primary material classification. Finally, this study explores a convolutional neural network model in a self-supervised Siamese setup with a large number of images that obtains an accuracy of 85% on the pretext task and an accuracy of 66% on the goal task to

关键词： Document analysis Image-based material analysis Historical manuscript Feature extraction Fourier transform Classification Clustering Convolutional neural network

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Simplified adaptive approach to efficient morphological image analysis

Simplified adaptive approach to efficient morphological imag...

引用

international conference on pattern recognition

作者： S. Fejes F. Vajda Department of Information Technology KFKI Research Institute of Measurement and Computing Techniques Budapest Hungary

In the paper adaptive application of morphological image processing is analysed and a simplified parameter modification technique is proposed. Based on a novel approach the number of control parameters ("filter-taps") of adaptive operations can be reduced if some a priori information about the input image is available. the convergency behavior and the prediction error of the new adaptation scheme is analyzed and compared to the classical approach. Finally, some applications of the proposed method is demonstrated.

关键词： Image analysis Image processing Morphology Information technology Adaptive filters Morphological operations Shape Runtime Information analysis Information filtering

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A maximum entropy approach to pairwise data clustering

A maximum entropy approach to pairwise data clustering

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international conference on pattern recognition

作者： J.M. Buhmann T. Hofmann Institut für Informatik III Universität Bonn Bonn Germany

Partitioning a set of data points which are characterized by their mutual dissimilarities instead of an explicit coordinate representation is a difficult, NP-hard combinatorial optimization problem. the authors formulate this optimization problem of a pairwise clustering cost function in the maximum entropy framework using a variational principle to derive corresponding data partitionings in a d-dimensional Euclidian space. this approximation solves the embedding problem and the grouping of these data into clusters simultaneously and in a selfconsistent fashion.

关键词： Entropy Extraterrestrial measurements Embedded computing Symmetric matrices Cost function Data analysis Psychology Noise reduction Noise measurement Data visualization

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