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检索条件"任意字段=12th International Conference on Computing and Pattern Recognition, ICCPR 2023"

共 284 条记录，以下是161-170 订阅

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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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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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Scalable parallel processing design for real time handwritten OCR

Scalable parallel processing design for real time handwritte...

引用

international conference on pattern recognition

作者： A. Cuhadar A.C. Downton Electronic Systems Engineering Department University of Essex Colchester UK

this paper presents a generalised technique for parallelising embedded computer vision and pattern recognition applications and shows how it has been applied to the recognition of handwritten postcodes on envelopes. the technique is based upon the utilisation of pipelines of processor farms (PPF), and is applicable to any embedded system with continuous input/output data streams. the postcode recogniser combines temporal multiplexing and data parallelism to achieve a speedup of 21.4 compared with the original sequential application, using a total of 52 transputers.

关键词： Parallel processing Process design Optical character recognition software Pipelines Dictionaries Handwriting recognition Concurrent computing throughput Systems engineering and theory Computer vision

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Affine reconstruction from perspective image pairs obtained by a translating camera

Affine reconstruction from perspective image pairs obtained ...

引用

international conference on pattern recognition

作者： L. Van Gool T. Moons M. Proesmans M. Van Diest ESAT Katholieke Univ. Leuven Belgium Katholieke Universiteit Leuven Belgium Katholieke Universiteit Leuven Leuven Flanders BE

the three-dimensional structure of a scene consisting of at least five points whose images are identified in two perspective views obtained by a translating camera, can be reconstructed up to a 3D affine transformation. Hence, a more detailed reconstruction is possible using less information when compared to the results for arbitrary stereo pairs taken with uncalibrated, perspective cameras.

关键词： Image reconstruction Cameras Layout Stereo image processing Moon Data mining Cloud computing Calibration Robot vision systems Mobile robots

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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...

引用

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

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

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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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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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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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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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