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Label Propagation Adaptive Resonance Theory for Semi-Supervised Continuous Learning

Taehyeong Kim, Injune Hwang, Gi-Cheon Kang, Won-Seok Choi, Hyunseo Kim, Byoung-Tak Zhang
2020 ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
In this paper, we propose Label Propagation Adaptive Resonance Theory (LPART) for semi-supervised continuous learning.  ...  Semi-supervised learning and continuous learning are fundamental paradigms for human-level intelligence.  ...  ADAPTIVE RESONANCE THEORY ART is a self-organizing neural network inspired by the brain information processing mechanisms.  ... 
doi:10.1109/icassp40776.2020.9054655 dblp:conf/icassp/KimHKCKZ20 fatcat:gybxtsof5fgkdfdqi5z3nltaq4

An Intelligent Ballistocardiographic Chair using a Novel SF-ART Neural Network and Biorthogonal Wavelets

Alireza Akhbardeh, Sakari Junnila, Teemu Koivistoinen, Alpo Värri
2006 Journal of medical systems  
This paper presents a comparative analysis of novel supervised fuzzy adaptive resonance theory (SF-ART), multilayer perceptron (MLP) and Multi Layer Perceptrons (MLP) neural networks over Ballistocardiogram  ...  learning around half second), and very low computational load compared to the well-known neural networks such as MLP which needs minutes to learn the training material.  ...  In our previous work, we proposed a novel neural network called Supervised Fuzzy Adaptive Resonance Theory (SF-ART) [11] which enables Fuzzy Adaptive Resonance Theory (F-ART) [18] for supervised incremental  ... 
doi:10.1007/s10916-006-9044-x pmid:17283924 fatcat:w7neqo7n2vhlrdokpcqh4h3vvm

Intelligence Through Interaction: Towards a Unified Theory for Learning [chapter]

Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg
2007 Lecture Notes in Computer Science  
This paper presents a learning architecture within which a universal adaptation mechanism unifies a rich set of traditionally distinct learning paradigms, including learning by matching, learning by association  ...  Through a case study on a minefield navigation domain, we illustrate the efficacy of the proposed model, the learning paradigms encompassed, and the various types of knowledge learned.  ...  The model unifies a number of network designs, most notably Adaptive Resonance Theory (ART) [3, 5] , Adaptive Resonance Associative Map (ARAM) [16] and Fusion Architecture for Learning, COgnition, and  ... 
doi:10.1007/978-3-540-72383-7_128 fatcat:2qwsva5ujvfahlzwntn4mfer2u

Fuzzy Logic Based Adaptive Resonance Theory-1 Approach for Offline Signature Verification

Charu Jain, Priti Singh, Ajay Rana
2017 Image Processing & Communications  
This paper presents the use fuzzy logic with adaptive resonance theory-1 in signature verification.  ...  Training and verification was done using fuzzy adaptive resonance theory-1(FART-1). The system is trained and verified for different datasets to increase the accuracy of the classifier.  ...  This step starts with training through adaptive resonance theory neural network.  ... 
doi:10.1515/ipc-2017-0015 fatcat:dz7y4tpqsvefjofke653lkgq3e

A Neural Architecture Based on the Adaptive Resonant Theory and Recurrent Neural Networks

Flávio Henrique Vieira Teles, Luan Ling Lee
2007 International Journal of Computer Science and Applications  
This neural architecture consists of a combination of an ART2 (Adaptive Resonance Theory) neural network and recurrent neural networks.  ...  In this paper, we propose a novel neural architecture that adaptively learns an input-output mapping using both supervised and non-supervised trainings.  ...  Introduction The Adaptive Resonance Theory (ART) was introduced as a theory for human cognitive information processing [1] .  ... 
dblp:journals/ijcsa/TelesL07 fatcat:r76t7jlytvh7nah6vvh4xhx4py

Manufacturing quality control by means of a Fuzzy ART network trained on natural process data

Massimo Pacella, Quirico Semeraro, Alfredo Anglani
2004 Engineering applications of artificial intelligence  
In this paper, a neural network system, which is based on an unsupervised training phase, is presented for quality control.  ...  In particular, the adaptive resonance theory (ART) has been investigated in order to implement a model-free quality control system, which can be exploited for recognising changes in the state of a manufacturing  ...  The proposed approach is based on the adaptive resonance theory (ART) neural network that is capable of fast, stable and cumulative learning.  ... 
doi:10.1016/j.engappai.2003.11.005 fatcat:sh5ftyqcubblzplfkhb7ptw6nq

Real Time Intrusion Detection System Using Computational Intelligence and Neural Network: A Review

Dr. Prabha Shreeraj Nair
2017 International Journal of Trend in Scientific Research and Development  
The computational intelligence describe based on following parameters such as computational speed, adaptation, error resilience and fault tolerance.  ...  A good intrusion detection system must be satisfied adaptable as requirements.  ...  A.2.2 Adaptive resonance theory (ART) The adaptive resonance theory is capable of handle wide spread of neural network models in terms of pattern recognition, efficiency of unsupervised/ supervised learning  ... 
doi:10.31142/ijtsrd5781 fatcat:52ngdo3qrvg5lmhbmnlk4hd7ai

A new ART-counterpropagation neural network for solving a forecasting problem

Tzu-Chiang Liu, Rong-Kwei Li
2005 Expert systems with applications  
This study presents a novel Adaptive resonance theory-Counterpropagation neural network (ART-CPN) for solving forecasting problems.  ...  The network is based on the ART concept and the CPN learning algorithm for constructing the neural network.  ...  ART-CPN based on Adaptive Resonance Theory and CPN that is supervised real-time learning by a self-organizing neural network.  ... 
doi:10.1016/j.eswa.2004.08.006 fatcat:neyiuu6cf5h7fpufdk7ddq4l3m

Page 903 of Psychological Abstracts Vol. 79, Issue 2 [page]

1992 Psychological Abstracts  
Neural Networks, 1991, Vol 4(4), 493-504. —Intro- duces a subclass of adaptive resonance theory (ART) architec- tures called ART 2-A.  ...  —Makes accessible the adaptive resonance theory (ART2) architecture (a mathematical and biological ex- tension of competitive learning) by focusing on ART2’s cluster- ing function and contrasting it with  ... 

Self-generation ART Neural Network for Character Recognition [chapter]

Taekyung Kim, Seongwon Lee, Joonki Paik
2006 Lecture Notes in Computer Science  
In this paper, we present a novel self-generation, supervised character recognition algorithm based on adaptive resonance theory (ART) artificial neural network (ANN) and delta-bar-delta method.  ...  The proposed method can extend itself based on new information contained in input patterns that require nodes of hidden layers in neural networks and effectively find characters.  ...  supported by Korean Ministry of Science and Technology under the National Research Laboratory Project, Korean Ministry of Information and Communication under HNRC-ITRC program at Chung-Ang university supervised  ... 
doi:10.1007/11760023_41 fatcat:ksngqhnx4ra5ndjg36c6s3lebm

Adaptive resonance theory based neural networks ? the ?ART? of real-time pattern recognition in chemical process monitoring?

1995 TrAC. Trends in analytical chemistry  
The family of artificial neural networks based on Adaptive Resonance Theory (ART) forms a collection of distinct mathematical patternrecognition methods.  ...  They include its use as a built-in detector for outliers, its rapid training speed, self-organizational behaviour, full chemical interpretability, and real-time and on-line applicability.  ...  Introduction Adaptive Resonance Theory (ART) based neural networks were introduced by Grossberg [ 1, 2] as rather theoretical neural models, describing selected aspects of the classification behaviour  ... 
doi:10.1016/0165-9936(95)90918-d fatcat:vkbos4cljffkzbvba5tq5asphy

Neural Network Techniques for Cancer Prediction: A Survey

Shikha Agrawal, Jitendra Agrawal
2015 Procedia Computer Science  
Neural networks are currently a burning research area in medical science, especially in the areas of cardiology, radiology, oncology, urology and etc.  ...  In this paper, we are surveying various neural network technologies for classification of cancer.  ...  a Subtype of Lymphoma Based on Gene Expression Profile New cancer diagnosis modeling using boosting and projective adaptive resonance theory with improved reliable index" Cancer classification using  ... 
doi:10.1016/j.procs.2015.08.234 fatcat:mej6gtx5gzhz3ei27koahpgn4e

Measurement Data Processing with the Use of Art Networks

Maria Mrówczyńska, Jacek Sztubecki
2018 Civil and Environmental Engineering Reports  
ART (Adaptive Resonance Theory) networks were invented in the 1990s as a new approach to the problem of image classification and recognition.  ...  ART networks belong to the group of resonance networks, which are trained without supervision.  ...  ART NETWORK TRAINING AND OPERATION SCHEME ART neural networks are trained without supervision and based on the adaptation resonance theory.  ... 
doi:10.2478/ceer-2018-0029 fatcat:sevwlyllmjaizcivkstsljauma

Beyond backprop: emerging trends in connectionist models of development: an introduction

Matthew Schlesinger, Domenico Parisi
2004 Developmental Science  
Many of these models rely on the backpropagation-of-error learning algorithm, a form of supervised learning in which a 'teacher' shapes the output of the network by providing it with desired responses.  ...  The third paper, by Maartje Raijmakers and Peter Molenaar, provides an overview of adaptive resonance theory (ART).  ... 
doi:10.1111/j.1467-7687.2004.00329.x fatcat:re4c7ojcuzhnxbupl35yivw73m

Page 2635 of Psychological Abstracts Vol. 79, Issue 6 [page]

1992 Psychological Abstracts  
—Discusses adaptive resonance theory | (ART1), which can be used to learn recognition categories and was derived and analyzed by G. A. Carpenter and S. Grossberg (1987).  ...  —Studied the role of supervised and un- supervised neura! learning schemes in the adaptive control of nonlinear dynamic systems.  ... 
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