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A fuzzy approach to texture segmentation

M. Hanmandlu, V.K. Madasu, S. Vasikarla
2004 International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004.  
To segment the texture image, the modified mountain clustering that is unsupervised and Fuzzy C-means clustering have been used.  ...  For this purpose, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window.  ...  Inclusion of a new cluster does not pose any problem in this clustering approach as against fuzzy C-means clustering where the clustering has to be done all over again.  ... 
doi:10.1109/itcc.2004.1286537 dblp:conf/itcc/HanmandluMV04 fatcat:fxu7n74lcjb4th4jwmbk5kpe3i

EEG based Cognitive State Analysis using Enhanced Convolutional Neural Network

2020 International Journal of Engineering and Advanced Technology  
Feature extraction for determination of concentration levels is done by applying fuzzy fractal dimension measures and Discrete Wavelet Transform(DWT) on the processed signals.  ...  feedback model to regulate this cognitive state.  ...  Fuzzy fractal dimension measure is used for clustering and provide extracted parameters in dimensions.  ... 
doi:10.35940/ijeat.d6915.049420 fatcat:jqqgdveff5ainetfq4uuxgqdqa

Unsupervised learning of Swiss population spatial distribution

Mikhail Kanevski
2021 PLoS ONE  
The approach is very powerful and provides a comprehensive local information about density and homogeneity/fractality of spatially distributed point patterns.  ...  The research methodology is based on the development of a high dimensional feature space by calculating local growth curves, widely used in fractal dimension estimation and on the application of clustering  ...  Acknowledgments The author would like to acknowledge Swiss Federal Office of Statistics and University of Lausanne for the access to population data and Federal Office of Topography (Swisstopo) for geographical  ... 
doi:10.1371/journal.pone.0246529 pmid:33571272 pmcid:PMC7877650 fatcat:akwgt35v6ra3rmnduaffhzr2jm

Development of the subsystem of forecasting for the system of marketing information management at an industrial enterprise

Mykhailo Oklander, Tatyana Oklander, Irina Pedko, Oksana Yashkina
2017 Eastern-European Journal of Enterprise Technologies  
A fuzzy method of hierarchy analysis and a multicriteria approach for fuzzy decision-making expansion are used to analyze such a system.  ...  Cluster analysis. Cluster analysis is a class of methods used to classify objects or events in relatively homogeneous groups called clusters Segmentation of the market.  ...  An enterprise receives forecasts of prices for raw materials, materials, semi-finished products, components with the help of fractal analysis.  ... 
doi:10.15587/1729-4061.2017.111547 fatcat:a5264n77jrfnxdstd7ngbzsy64

An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities

Hai Wang, Zeshui Xu, Witold Pedrycz
2017 Knowledge-Based Systems  
Fuzzy sets have been employed for big data processing due to their abilities to represent and quantify aspects of uncertainty.  ...  Several innovative approaches within the framework of Granular Computing have been proposed.  ...  Acknowledgments The authors would like to thank the Editor-in-Chief and four anonymous reviewers for their insightful and constructive commendations that have led to an improved version of this paper.  ... 
doi:10.1016/j.knosys.2016.11.008 fatcat:i2ay7ugn5rfkhmz7jw6hyc67fm

Monitoring crystal growth based on image texture analysis using wavelet transformation

B. Zhang, A. Abbas, J.A. Romagnoli
2012 IFAC Proceedings Volumes  
Wavelet-fractal and energy signatures are performed afterwards to estimate texture on crystal clusters.  ...  Digital image texture analysis is a promising method in monitoring and control systems, and is becoming increasingly more attractive due to availability of high speed imaging devices and equally powerful  ...  A multi-resolution fuzzy clustering approach was proposed to segment the touching areas between particles (Zhang, Abbas and Romagnoli 2011) .  ... 
doi:10.3182/20120710-4-sg-2026.00027 fatcat:nrsjy44eebbzvonay6fx4khje4

Mapping Evaluation for Semantic Browsing

Veslava Osinska, Adam Jozwik, Grzegorz Osinski
2015 Proceedings of the 2015 Federated Conference on Computer Science and Information Systems  
For the quantitative analysis the authors used machine learning and pattern recognition algorithms and described: clusterization degree, fractal dimension and lacunarity.  ...  Local density differences, clusterization, homogeneity, and gappiness were measured to show the most acceptable layout for an analysis, perception and exploration processes.  ...  Dynamical characteristics of clustering are crucial for a final evaluation of the presented approaches in terms of structural analysis.  ... 
doi:10.15439/2015f50 dblp:conf/fedcsis/OsinskaJO15 fatcat:ropgrgv5n5fzbd673637wdr7by

Artificial Intelligence for Forecasting the Prevalence of COVID-19 Pandemic: An Overview

Ammar H. Elsheikh, Amal I. Saba, Hitesh Panchal, Sengottaiyan Shanmugan, Naser A. Alsaleh, Mahmoud Ahmadein
2021 Healthcare  
Both statistical and artificial intelligence (AI) approaches have been reported; however, the AI approaches showed a better accuracy compared with the statistical approaches.  ...  This study presents a review on the applications of different AI approaches used in forecasting the spread of this pandemic.  ...  Approach Hybrid fractal-fuzzy approach (HFFA) us a hybrid approach in which fuzzy logic is integrated with fractal theory.  ... 
doi:10.3390/healthcare9121614 pmid:34946340 pmcid:PMC8700845 fatcat:6wueathck5cvdcs2ul5kxtdozu

Spatio-temporal Smoke Clustering in Outdoor Scenes Based on Boosted Random Forests

Margarita Favorskaya, Anna Pyataeva, Aleksei Popov
2016 Procedia Computer Science  
The main problem of the early smoke detection is to obtain the low values of the clustering errors.  ...  Our contribution deals with a reasonable clustering of the smoke/non-smoke regions based on the Boosted Random Forests (BRFs).  ...  This approach combines a robustness of multiple classifier systems, a power of the randomness to increase the diversity of the trees, and a flexibility of fuzzy logic and fuzzy sets.  ... 
doi:10.1016/j.procs.2016.08.231 fatcat:eoypid2cn5cibd662oiqsyhzr4

Enhanced Fuzzy K-NN Approach for Handling Missing Values in Medical Data Mining

R. Naveen Kumar, M. Anand Kumar
2016 Indian Journal of Science and Technology  
Objectives: Exploratory data study is regularly indispensable to evaluate a potential premise for the subsequent studies such as grouping the data in clusters or diversifying the data in classification  ...  Application/Improvements: As compared to other techniques the proposed fuzzy based K-NN gives high inconsistency.  ...  When there is a vagueness in handling the missing values using traditional imputation 12 methods which leads to misclassification and misconception of the pattern analysis that may leads to false alarms  ... 
doi:10.17485/ijst/2016/v9is1/94094 fatcat:zoy5jxhetvd6vojo6luyjhpgam

An Overview of the Research on Plant Leaves Disease detection using Image Processing Techniques

Ms. Kiran R. Gavhale, Prof. Ujwalla Gawande
2014 IOSR Journal of Computer Engineering  
Farmers experience great difficulties in switching from one disease control policy to another.  ...  Now a day's plant diseases detection has received increasing attention in monitoring large field of crops.  ...  It is then refined by fuzzy cmeans clustering [6] . It applied to any multispectral images is a major advantage [7] .Segmentation approach for region growing is k-means clustering.  ... 
doi:10.9790/0661-16151016 fatcat:3qli4sibp5aszoogqcabwm7fa4

Detection of Lung Nodules on Medical Images by the Use of Fractal Segmentation

Afsaneh Abdollahzadeh Rezaie, Ali Habiboghli
2017 International Journal of Interactive Multimedia and Artificial Intelligence  
Thresholding was performed by the use of FCM method which is the fuzzy c-means clustering. FCMTHRESH thresholding was done by 3-class fuzzy c-means clustering.  ...  They conducted a fractal analysis of the square chest images using the virtual volume method.  ... 
doi:10.9781/ijimai.2017.452 fatcat:paskh52d6zhrtfuf3w37lbacey

Neural Network Based Texture Analysis Of Liver Tumor From Computed Tomography Images

K.Mala, V.Sadasivam, S.Alagappan
2008 Zenodo  
As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis.  ...  Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors  ...  [7] proposed a CAD system based on texture features estimated from Gray Level Difference Statistics (GLDS), SGLDM, Fractal Dimension (FD) and a novel fuzzy neural network classifier to classify a liver  ... 
doi:10.5281/zenodo.1061402 fatcat:kfzrusbcpvel3eqvoyqip6zkee

Chaotic Time Series Forecasting Approaches Using Machine Learning Techniques: A Review

Bhukya Ramadevi, Kishore Bingi
2022 Symmetry  
This tendency permeates and promotes many subjects. As a result, chaos research has access to a solution. In the meantime, chaos theory applications are becoming increasingly popular.  ...  Fuzzy with ANN-Based Forecasting Approaches FNN is a hybrid network developed using ANN's learning ability and fuzzy logic's noise handling capability.  ... 
doi:10.3390/sym14050955 dblp:journals/symmetry/RamadeviB22 fatcat:3oa3go7rdzdurjl4yxcivjsbf4

An Approach to Determining the Spatially Contiguous Zone of a Self-Organized Urban Agglomeration

Fei Liu, Qing Huang
2019 Sustainability  
This approach will prove to be a useful reference for the identification of spatial ranges in future studies.  ...  From the perspective of the assumption that the space of urban agglomerations is molecule like assembled, and through the extraction and analysis of spatial fractals, we present an objective method to  ...  Acknowledgments: We would like to thank Nianjue Wang and Xinqi Zheng for their review and supervision. We would also like to thank for providing help with the language.  ... 
doi:10.3390/su11123490 fatcat:7rlyg3qtabeo5bltcd25r4jrk4
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