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A What-and-Where fusion neural network for recognition and tracking of multiple radar emitters

Eric Granger, Mark A. Rubin, Stephen Grossberg, Pierre Lavoie
2001 Neural Networks  
Other modifications improved classification of data that include missing input pattern components and missing training classes.  ...  Fuzzy ARTMAP was combined with a bank of Kalman filters to group pulses transmitted from different emitters based on their position-specific parameters, and with a module to accumulate evidence from fuzzy  ...  As pointed out by Carpenter and Markuzon ( 1998) , MT-is a better algorithmic approximation to the continuous-time version of fuzzy ARTMAP. Classification of Incomplete Data.  ... 
doi:10.1016/s0893-6080(01)00019-3 pmid:11341569 fatcat:tfnjmve2izduji3jebetf6kgyu

A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning

Eric Granger, Jean-Francois Connolly, Robert Sabourin
2008 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)  
Training fuzzy ARTMAP and Gaussian ARTMAP through incremental learning often requires fewer training epochs to converge, and leads to more compact networks.  ...  The advantages and drawbacks of these architectures are discussed for incremental learning with different data block sizes and data set structures.  ...  INTRODUCTION F OR a wide range of applications, machine learning represents a cost-effective and practical approach to the design of pattern classification systems.  ... 
doi:10.1109/ijcnn.2008.4634267 dblp:conf/ijcnn/GrangerCS08 fatcat:uoaogruvzzcftnquspewo45jju

Clustering-Based Hybrid Approach for Multivariate Missing Data Imputation

Aditya Dubey, Akhtar Rasool
2020 International Journal of Advanced Computer Science and Applications  
The K-means clustering technique along with the weighted KNN makes efficient imputation of the missed value. The results are compared against imputations by mean substitution and Fuzzy C Means (FCM).  ...  In the era of big data, a significant amount of data is produced in many applications areas.  ...  Lim et al. suggested a hybrid neural network technique that utilizes the ARTMAP and fuzzy c-means clustering for classifying the patterns utilizing the incomplete training and testing dataset [17] .  ... 
doi:10.14569/ijacsa.2020.0111186 fatcat:espubzgr2nedxd3yeo6ipb5skq

Estimation of infinite dilution activity coefficients of organic compounds in water with neural classifiers

Francesc Giralt, G. Espinosa, A. Arenas, J. Ferre-Gine, L. Amat, X. Gironés, R. Carbó-Dorca, Y. Cohen
2004 AIChE Journal  
The use of only four molecular quantum similarity measures proved to be sufficient for building a ln␥ ϱ fuzzy-ARTMAP-based QSPR with reasonable accuracy.  ...  The resulting fuzzy-ARTMAP-based QSPRs performed with errors that were on the average seven times smaller compared to previous published models.  ...  Molecular Descriptors and Experimental Aqueous Infinity Dilution Activity Coefficients for the Data Set of 325 Organic Compounds* (Continued) AIChE Journal  ... 
doi:10.1002/aic.10116 fatcat:ltn4nefuj5es7je75og4xuut5u

An adaptive classification system for video-based face recognition

Jean-François Connolly, Eric Granger, Robert Sabourin
2012 Information Sciences  
The ACS needs several training sequences to produce the optimal solution, and adapting fuzzy ARTMAP parameters according to classification rate tends to require more category neurons and training epochs  ...  For instance, in biometric systems, new data may be acquired and used to enroll or to update knowledge of an individual.  ...  The grid optimization method was applied with a 100 Â 100 grid, instead of PSO, and for each point on the grid, f ðh; tÞ was estimated by the average classification rate of fuzzy ARTMAP on the IIT-NRC  ... 
doi:10.1016/j.ins.2010.02.026 fatcat:xh26zy3r2bdyhp2vqag4nntvwu

Application of the fuzzy ARTMAP neural network model to medical pattern classification tasks

Joseph Downs, Robert F. Harrison, R.Lee Kennedy, Simon S. Cross
1996 Artificial Intelligence in Medicine  
This paper presents research into the application of the fuzzy ARTMAP neural network model to medical pattern classification tasks.  ...  of input features to pattern classes.  ...  Acknowledgements Thanks to K.L. Woods of the Department of Pharmacology, University of Leicester, UK for providing the coronary care patient data used in Section 3.  ... 
doi:10.1016/0933-3657(95)00044-5 pmid:8870968 fatcat:lflbnf4qybcctibgqnelehap4y

Artificial intelligence in medicine

1989 Data & Knowledge Engineering  
This paper presents research into the application of the fuzzy ARTMAP neural network model to medical pattern classification tasks.  ...  of input features to pattern classes.  ...  Acknowledgements Thanks to K.L. Woods of the Department of Pharmacology, University of Leicester, UK for providing the coronary care patient data used in Section 3.  ... 
doi:10.1016/0169-023x(89)90023-2 fatcat:swl3wjqhobcqhoz5vltr7xzk6a

Artificial intelligence in medicine

1995 Artificial Intelligence in Medicine  
This paper presents research into the application of the fuzzy ARTMAP neural network model to medical pattern classification tasks.  ...  of input features to pattern classes.  ...  Acknowledgements Thanks to K.L. Woods of the Department of Pharmacology, University of Leicester, UK for providing the coronary care patient data used in Section 3.  ... 
doi:10.1016/0933-3657(95)90009-8 fatcat:5ahpds77lzfqvbmdz5tizka5c4

Artificial intelligence in medicine

1989 American Journal of Hematology  
This paper presents research into the application of the fuzzy ARTMAP neural network model to medical pattern classification tasks.  ...  of input features to pattern classes.  ...  Acknowledgements Thanks to K.L. Woods of the Department of Pharmacology, University of Leicester, UK for providing the coronary care patient data used in Section 3.  ... 
doi:10.1002/ajh.2830320222 fatcat:vk7arl46fnad7i5p3it6rrdriq

An Overview and Recent Advances in Fuzzy ARTMAP Classifier Usage for Mapping Purposes Using Remotely Sensed Data

P. F. Prado, Department of Earth Physics and Thermodynamics, University of Valencia, Valencia, Valencian Community 50 46100, Spain, I. C. S. Duarte, Department of Biology, Federal University of São Carlos, Sorocaba, São Paulo 18052-780, Brazil
2020 Journal of Environmental Informatics Letters  
This paper presents an overview and recent advances on the usage of Fuzzy ARTMAP artificial neural network architecture (and its variants) for mapping purposes using remotely sensed data.  ...  Possible gaps in the literature related to Fuzzy ARTMAP classifier usage for mapping are suggested, leading to paths for future developments in this field of research.  ...  of the fuzzy ARTMAP neural network model to medical pattern classification tasks 81 Artificial Intelligence in Medicine 2 Mannan 1998 Fuzzy ARTMAP supervised classification of multi-spectral  ... 
doi:10.3808/jeil.202000032 fatcat:2havklimhng5nd7ywda6sr452y

Neuro-fuzzy Based Analysis of Hyperspectral Imagery

Fang Qiu
2008 Photogrammetric Engineering and Remote Sensing  
In this paper, GFLVQ was further improved to efficiently and effectively process hyperspectral data through training data informed initialization and a simplified fuzzy learning algorithm.  ...  GFLVQ is both a fuzzy neural network and a neural fuzzy system with supervised learning and unsupervised self-organizing capabilities.  ...  Caiyun Zhang assisted in great deal in the implementation and application of the improved system. Mr. Shaofei Chen provided assistance in classification accuracy assessment, and Mr.  ... 
doi:10.14358/pers.74.10.1235 fatcat:x4nd5pwrszhtjpldew2gcwrgmy

Automation of DNA Finger Printing for Precise Pattern Identification using Neural fuzzy Mapping approach

A. Pushpalatha, B. Mukunthan
2011 International Journal of Computer Applications  
became manually impractical with the growing amount of data.  ...  The perfect blend made of bioinformatics, neural networks and fuzzy logic results in efficient algorithms of pattern analysis techniques that induce automation which is inevitable in DNA profiling that  ...  The authors would like to thank Dr.K.Somasundaram at Amrita University, Coimbatore and Dr.N.Nagaveni at Coimbatore Institute of Technology, Coimbatore for their help in conducting the experiments.  ... 
doi:10.5120/1761-2411 fatcat:v3rpztzcmzanbier6laac4fbi4

Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review

Swapan Talukdar, Pankaj Singha, Susanta Mahato, Shahfahad, Swades Pal, Yuei-An Liou, Atiqur Rahman
2020 Remote Sensing  
(Fuzzy ARTMAP), spectral angle mapper (SAM) and Mahalanobis distance (MD) were examined.  ...  Since quantitative assessment of changes in LULC is one of the most efficient means to understand and manage the land transformation, there is a need to examine the accuracy of different algorithms for  ...  unsupervised classification techniques include Affinity Propagation (AP) cluster algorithm, fuzzy c-means algorithms, K-means algorithm, ISODATA (iterative self-organizing data) etc  ... 
doi:10.3390/rs12071135 fatcat:ayfutsgwzjhtxk3ysbpj4q2t7q

Delineation of Techniques to Implement on the Enhanced Proposed Model Using Data Mining for Protein Sequence Classification

Ananya Basu, Suprativ Saha
2014 International Journal of Database Management Systems  
Issues like managing noisy and incomplete data are needed to be dealt with. Use of data mining in biological domain has made its inventory success.  ...  In post genomic era with the advent of new technologies a huge amount of complex molecular data are generated with high throughput.  ...  Then a pattern matrix using the feature value is formed. Finally the fuzzy ARTMAP [6] [7] [9] model is applied and matched with the knowledge database.  ... 
doi:10.5121/ijdms.2014.6105 fatcat:wo3wz57hcnh7hkfxpqnprxkuse

Delineation of Techniques to Implement on the Enhanced Proposed Model Using Data Mining for Protein Sequence Classification

Ananya Basu, Suprativ Saha
2014 International Journal of Database Management Systems  
Issues like managing noisy and incomplete data are needed to be dealt with. Use of data mining in biological domain has made its inventory success.  ...  In post genomic era with the advent of new technologies a huge amount of complex molecular data are generated with high throughput.  ...  Then a pattern matrix using the feature value is formed. Finally the fuzzy ARTMAP [6] [7] [9] model is applied and matched with the knowledge database.  ... 
doi:10.5121/ijdms.2013.6105 fatcat:x2jkmr7iavfnfcnsb6e4qjj4yy
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