Articles listed below give examples of ART-based systems being used outside the CNS department at Boston University.
| Categories |
Topics:
Machine Learning,
Applications:
Industrial Control,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Pacella, M. |
Semeraro, Q. |
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| Abstract |
Neural networks have recently received a great deal of attention in the field of manufacturing process quality control, where statistical techniques have traditionally been used. In this paper, a neural-based procedure for ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Industrial Control,
Models:
ART 1, |
| Author(s) |
Haq, A.N. |
Venkumar, P. |
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| Abstract |
The primary objective of group technology (GT) is to enhance the productivity in the batch manufacturing environment. The GT cell formation problem is solved using modified binary adaptive resonance theory networks known as ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Other,
Models:
ART 2 / Fuzzy ART,
Self Organizing Maps, |
| Author(s) |
Lee, K.H. |
Ong, S.H. |
Venkatesh, Y.V. |
Yeo, N.C. |
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| Abstract |
We propose a new competitive-learning neural network model for colour image segmentation. The model, which is based on the adaptive resonance theory (ART) of Carpenter and Grossberg and on the self-organizing map (SOM) of ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Other,
Models:
ART 2 / Fuzzy ART,
Self Organizing Maps, |
| Author(s) |
Fong, A.C.M. |
Fong, B. |
Hong, G.Y. |
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| Abstract |
Purpose - We describe an intelligent video categorization engine (IVCE) that uses the learning capability of artificial neural networks (ANNs) to classify suitably preprocessed video segments into a predefined number of ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Medical Diagnosis,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Komorowski, D. |
Kostka, P.S. |
Tkacz, E.J. |
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| Abstract |
Feature extraction and selection method as a preliminary stage of heart rate variability (HRV) signals unsupervised learning neural classifier is presented. Multi-domain, mixed new feature vector is created from time, ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Industrial Control,
Models:
ART 1,
ART 2 / Fuzzy ART,
Genetic Algorithms, |
| Author(s) |
Chen Y.M. |
Chen, Y.J. |
Chu, H.C. |
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| Abstract |
Engineering design is a complex activity, and is heavily reliant on the know-how of engineering designers. Hence, capturing, storing, and reusing design information, design intent, and underlining design knowledge to support ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Medical Diagnosis,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Honda, H. |
Kobayashi, T. |
Takahashi, H. |
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| Abstract |
We applied projective adaptive resonance theory (PART) to gene screening for DNA microarray data. Genes selected by PART were subjected to our FNN-SWEEP modeling method for the construction of a cancer class prediction ... |
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| Categories |
Topics:
Machine Learning,
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| Author(s) |
Daniell, C. |
Srinivasan, N. |
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| Abstract |
A plurality of image chips (202) (over 100), each of the chips containing the same, known target of interest, such as, for example an M109 tank are presented to the system for training. Each image chip of the known target is ... |
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| Categories |
Topics:
Machine Learning,
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| Author(s) |
Kumar, A. |
Shetty, R.K. |
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| Abstract |
A technique for clustering input data includes receiving data and reading a sample of the received data having a predetermined window length. The technique further includes checking the read sample of data for uncertainty ... |
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| Categories |
Topics:
Machine Learning,
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| Author(s) |
Meng, Z. |
Pao, Y.H. |
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| Abstract |
The subject system provides reduced-dimension mapping of pattern data. Mapping is applied through conventional single-hidden-layer feed-forward neural network with non-linear neurons. According to one aspect of the present ... |
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