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Static Field Approach for Pattern Classification [chapter]

Dymitr Ruta, Bogdan Gabrys
2002 Lecture Notes in Computer Science  
In our approach inspiration for the new classification method has been found in the physical world.  ...  Namely we considered training data as particles in the input space and exploited the concept of a static field acting upon the samples.  ...  Such a static field classification (SFC) resembles to a certain degree non-parametric density estimation based approaches for classification [1] . The remainder of the paper is organized as follows.  ... 
doi:10.1007/3-540-46019-5_18 fatcat:z5chxqkzafh6lk7kqvi7fqoliy

Malware Detection using Deep Learning Methods

2020 International Journal of Innovative Science and Modern Engineering  
The methods discussed here are combined static and dynamic approach, random forest, Bayes classification.  ...  Malware detection is a milestone in the field of computer security. For detecting malware many methods have been evolved.  ...  Here uses a machine learning approach based on Bayesian classification which uncover all unknown malwares through static analysis.  ... 
doi:10.35940/ijisme.f1218.046620 fatcat:fut3da7njbepxlcpogkonlz6ye

Spatio-temporal data classification through multidimensional sequential patterns: Application to crop mapping in complex landscape

Yoann Pitarch, Dino Ienco, Elodie Vintrou, Agnès Bégué, Anne Laurent, Pascal Poncelet, Michel Sala, Maguelonne Teisseire
2015 Engineering applications of artificial intelligence  
For this reason, there is a need for suitable data mining techniques for this source of data.  ...  In this work, we developed a data mining methodology to extract multidimensional sequential patterns to characterize temporal behaviors.  ...  Classification techniques based on frequent patterns have been adopted in [4, 5] .  ... 
doi:10.1016/j.engappai.2014.09.001 fatcat:ssvhy7vu6jbi5cxusacjgdc5vu

Description of Rotation-Invariant Textures using Local Binary Pattern Features

Prashant H.Gutte, Prashant K. Kharat
2014 International Journal of Computer Applications  
Uniform Local binary pattern (LBP) is a combination of structural and statistical analysis model for classification of both static and dynamic textures.  ...  Texture classification is one of the most interesting research topics in the field of computer vision. This paper aims at classifying static as well as dynamic textures (DT).  ...  Our approach for Rotation invariant static textures gives 77.01 percentage classification results as compare to other LBP based methods on OUTEX_TC_00012.  ... 
doi:10.5120/17404-7969 fatcat:dvqblydxmjfavhdjulxbnwpv6a

Metabolic connectivity-based single subject classification by multi-regional linear approximation in the rat

Maximilian Grosch, Leonie Beyer, Magdalena Lindner, Lena Kaiser, Seyed-Ahmad Ahmadi, Anna Stockbauer, Peter Bartenstein, Marianne Dieterich, Matthias Brendel, Andreas Zwergal, Sibylle Ziegler
2021 NeuroImage  
Overall, the classification accuracy with this method was 84.3% for 3 classes, 75.0% for 4 classes, and 54.1% for 5 classes and outperformed random classification as well as machine learning classification  ...  Classification in different stages after UL was performed by determining connectivity patterns for the different classes by Pearson's correlation between uptake values in atlas-based segmented brain regions  ...  We thank Katie Göttlinger for copyediting the manuscript and Astrid Gosewisch for valuable comments.  ... 
doi:10.1016/j.neuroimage.2021.118007 pmid:33831550 fatcat:nh7idwkmrzdi7bfm62lyfac7dq

Social Pedestrian Group Detection Based on Spatiotemporal-oriented Energy for Crowd Video Understanding

2018 KSII Transactions on Internet and Information Systems  
Extensive experiments on challenging datasets demonstrate that our method can achieve superior results for social pedestrian group detection and crowd video classification.  ...  One of the main challenges of social group detection arises from the complex dynamic variations of crowd patterns.  ...  Fig. 10 10 demonstrates the crowd video classification accuracy for each class compared with the approach in Fig. 10 . 10 Per-class accuracy comparison of crowd video classification using different methods  ... 
doi:10.3837/tiis.2018.08.012 fatcat:t6af4huptjfjhmcnmpodkfchoi

Temporal knowledge: Recognition and learning of time-based patterns

Chen-Han Sung
1988 Neural Networks  
SUBJECT TERMS (COw wonWr 0ed HICO&Weddorlby NOCAne) FIELD GROUP SUB-GROUP Gaussian classification temporal data recognition patterns learning patterns 19.  ...  Fields F1 and F2 constitute the static subsystem, an adaptive resonance system. Field F3 contains information based on the classifications made by F2, after decay and shunting.  ... 
doi:10.1016/0893-6080(88)90348-6 fatcat:2upwh2fn6jaqzi6pn2sx62bjii

Heterogeneous patterns enhancing static and dynamic texture classification

Núbia Rosa da Silva, Odemir Martinez Bruno
2013 Journal of Physics, Conference Series  
Results show that our method provides better classification rate compared with conventional approaches both in static and in dynamic texture.  ...  We find sub patterns of texture according to the scale and then group similar patterns for a more refined analysis. Tests were performed in four static texture databases and one dynamic one.  ...  Classification of patterns can be used in a variety of applications in different fields such as nanotechnology 1-4 , biology [5] [6] [7] [8] [9] , medicine 10 and computer science 11, 12 .  ... 
doi:10.1088/1742-6596/410/1/012033 fatcat:uuaigk6chne63dtqzpygsrfbea

Spatial Pattern of Glaucomatous Visual Field Loss Obtained with Regionally Condensed Stimulus Arrangements

Ulrich Schiefer, Eleni Papageorgiou, Pamela A. Sample, John P. Pascual, Bettina Selig, Elke Krapp, Jens Paetzold
2010 Investigative Ophthalmology and Visual Science  
Detailed knowledge about the spatial pattern and the local frequency distribution of glaucomatous VFDs is an essential prerequisite for creating regionally condensed stimulus arrangements for adequate  ...  a full-field perimeter.  ...  [25] [26] [27] [28] [29] [30] Previous pattern analyses based on static perimetry with enhanced test point density referred to the results of supraliminal static perimetry and, therefore, might have  ... 
doi:10.1167/iovs.09-5067 pmid:20538998 pmcid:PMC3061505 fatcat:7a2lz7n6bvhl5i2nk5nkaxxacy

Utilizing Automatic Recognition and Classification of Images for Pattern Recognition

Mohammad Hadi Yousofi
2014 International Journal of Intelligent Information Systems  
Pattern recognition is a scientific approach for categorizing objects to class or subject numbers.  ...  Occupation, automation, military information, communication, industry and commercial applications and many other fields can benefit from Pattern recognition approaches.  ...  Classification Algorithms (Algorithms with a Predictor Supervisor) The selected algorithm for recognizing patterns depend on the type of output, with or without supervision, and the static or dynamic nature  ... 
doi:10.11648/j.ijiis.s.2014030601.25 fatcat:n643vk7d6badtekl4khuxpmbqe

Neural attractor network for application in visual field data classification

Wolfgang Fink
2004 Physics in Medicine and Biology  
The purpose was to introduce a novel method for computer-based classification of visual field data derived from perimetric examination, that may act as a 'counsellor', providing an independent 'second  ...  In conclusion, the novel method for computer-based classification of visual field data, presented here, furnishes a valuable first overview and an independent 'second opinion' in judging perimetric examination  ...  Acknowledgment I would like to thank E W Schmid for scientific advice and valuable discussions. Application of neural networks in perimetry  ... 
doi:10.1088/0031-9155/49/13/003 pmid:15285248 fatcat:kjjbsmnhybdbbkvncpnmt6fukq

Improved Detection of Advanced Persistent Threats Using an Anomaly Detection Ensemble Approach

Adelaiye Oluwasegun Ishaya, Ajibola Aminat, Bisallah Hashim, Abiona Akeem Adekunle
2021 Advances in Science, Technology and Engineering Systems  
Our approach combines static rule anomaly detection through pattern recognition and machine learning-based classification technique in mitigating the APT. (1) The rules-based on patterns are derived using  ...  statistical analysis majorly Kruskal Wallis test for association.  ...  Using statistical analysis test for association, patterns to be used as a threshold for a static rule detection model can be gotten. These thresholds are set using rules S1, S2,….  ... 
doi:10.25046/aj060234 fatcat:x7knslhs2fc6th3uperurx7ey4

Single-Pixel Moving Object Classification with Differential Measuring in Transform Domain and Deep Learning

Manhong Yao, Shujun Zheng, Yuhang Hu, Zibang Zhang, Junzheng Peng, Jingang Zhong
2022 Photonics  
In order to improve the reliability of the classification results for fast-moving objects, we employed a measurement data rolling utilization approach for repeated classification.  ...  Thanks to the property that the natural images are sparse in the orthogonal transform domain, we used a small number of basis patterns of discrete-sine-transform to obtain feature information for classification  ...  In these reported methods, the object light field is modulated by using special patterns to obtain the feature information of objects for classification of static objects, such as Hadamard-transform basis  ... 
doi:10.3390/photonics9030202 fatcat:ymgz7wevnbhzhgfqir6zd4zwn4

Application of pattern recognition methods to automatic identification of microscopic images of rocks registered under different polarization and lighting conditions

Bartłomiej Ślipek, Mariusz Młynarczuk
2013 Geology Geophysics & Environment  
The classification was conducted with the use of four pattern recognition methods: nearest neighbor, k-nearest neighbors, nearest mode, and optimal spherical neighborhoods on thin sections of five selected  ...  The results show that the automatic classification of rocks is possible within a pre-defined group of rocks.  ...  usage of pattern recognition in various fields Pattern recognition is extensively used in various aspects of science and everyday life, also in Earth sciences.  ... 
doi:10.7494/geol.2013.39.4.373 fatcat:wgspaq6x75fgbchy6yjslallwu

Signal-carrying speckle in Optical Coherence Tomography: a methodological review on biomedical applications [article]

Vania Bastos Silva, Danilo Andrade De Jesus, Stefan Klein, Theo van Walsum, João Cardoso, Luisa Sánchez Brea, Pedro G. Vaz
2021 arXiv   pre-print
Approach: PubMed and Scopus databases were used to perform a systematic review on studies published until April 2021. From 134-screened studies, 37 were eligible for this review.  ...  The results show that features retrieved from speckle can be used successfully in different applications, such as classification and segmentation.  ...  PubMed was chosen for being one of the largest databases in the medical field, and Scopus for combining articles from both medical and technical fields.  ... 
arXiv:2108.13109v1 fatcat:e4z5hhygwbfbnf4exzzrerz3ve
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