Articles listed below give examples of ART-based systems being used outside the CNS department at Boston University.
| Categories |
Topics:
Machine Learning,
Applications:
Medical Diagnosis,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Ng, G.S. |
Quek, C. |
Razvi, K. |
Tan, T.Z. |
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| Abstract |
Early detection is paramount to reduce the high death rate of ovarian cancer. Unfortunately, current detection toot is not sensitive. New techniques such as deoxyribonucleic acid (DNA) micro-array and proteomics data are ... |
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| Categories |
Topics:
Machine Learning,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Lim, C.P. |
Rao, M.V.C. |
Tan, S.C. |
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| Abstract |
This paper presents a novel conflict-resolving neural network classifier that combines the ordering algorithm, fuzzy ARTMAP (FAM), and the dynamic decay adjustment (DDA) algorithm, into a unified framework. The hybrid ... |
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| Categories |
Topics:
Machine Learning,
Models:
ARTMAP,
Fuzzy ARTMAP, |
| Author(s) |
Lim, C.P. |
Abidin, I. Z. |
Yap, K.S. |
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| Abstract |
In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Chemical Analysis,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Hsieh, K.L. |
Yang, I.C. |
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| Abstract |
To recognize the DNA sequence and mine the hidden information to achieve the classification of organisms are viewed as a difficult work to biologists. As we know, the amino acids are the basic elements to construct DNA. ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Biological Classification,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Barat, J.M. |
Escriche, I. |
GarciaBreijo, E. |
Gil, L. |
MartinezManez, R. |
Soto, J. |
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| Abstract |
We report on the development of an electronic tongue as potential tool for fish freshness determination. The studies were carried out following the evolution with time on fillet of cultured sea bream (Sparus Auratus). The ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Market Research,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Chen, H-C. |
Shieh, M.D. |
Yan, W. |
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| Abstract |
Design knowledge acquisition plays an extremely important role in new product conceptualization and product redesign. This study aims at facilitating the effectiveness of product redesign activities. It involves two ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Biological Classification,
Models:
ART 2 / Fuzzy ART,
Self Organizing Maps, |
| Author(s) |
Gupta, S.D. |
Prasad, V.S.S. |
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| Abstract |
Photometric clustering of regenerated plants of gladiolus was described using fuzzy adaptive resonance theory (ART) and the resultant grouping pattern was compared with ART 2, and self-organizing map (SOM) neural network ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Medical Diagnosis,
Models:
ART 1, |
| Author(s) |
Honda, H. |
Kawamura, T. |
Takahashi, H. |
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| Abstract |
A significant problem in gene expression analysis is that the sample size is substantially lower than the number of genes. Bagging is an effective method of solving this problem in the case of small sample datasets. We have ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Other,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Lu, N. |
Tan, A. |
Xiao, D. |
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| Abstract |
This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Other,
Models:
ART 1,
Self Organizing Maps, |
| Author(s) |
Lughofer, E. |
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| Abstract |
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental online learning. This is motivated in the ... |
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