The merging of information from disparate sources with differing conceptual, contextual and typographical representations.
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Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is ... |
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This paper investigates the abilities of adaptive resonance theory (ART) neural networks as miners of hierarchical thematic structure in text collections. We present experimental results with binary ART1 on the benchmark ... |
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The NetFlix Prize is a research contest that will award $1 Million to the first group to improve NetFlix's movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of ... |
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Clustering is an important function in data mining. Its typical application includes the analysis of consumer s materials. Adaptive resonance theory network (ART) is very popular in the unsupervised neural network. Type I ... |
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Document clustering is a very useful application in recent days especially with the advent of the World Wide Web. Most of the existing document clustering algorithms either produce clusters of poor quality or are highly ... |
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The World Wide Web has become an important medium for disseminating scientific publications. Many publications are now made available over the Web. However, existing search engines are ineffective in searching these ... |
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An adaptive-resonance theory (ART)-based fuzzy controller is presented for the adaptive navigation of a quadruped robot in cluttered environments, by incorporating the capability of ART in stable category recognition into ... |
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Detecting critical changes of environments while driving is an important task in driver assistance systems. In this paper, a computational model motivated by human cognitive processing and selective attention is proposed for ... |
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This paper aims to show how we can make progress in elucidating how people understand speech by changing our focus of inquiry from abstraction of formal units of linguistic analysis to a detailed analysis of global aspects ... |
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Segmentation is a fundamental step in image description or classification. In recent years, several computational models have been used to implement segmentation methods but without establishing a single analytic solution. ... |
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Mobile robots must be able to build their own maps to navigate in unknown worlds. Expanding a previously proposed method based on the fuzzy ART neural architecture (FARTNA), this paper introduces a new online method for ... |
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This paper proposes a methodology to optimize the future accuracy of a collaborative recommender application in a citizen Web portal. There are four stages namely, user modeling, benchmarking of clustering algorithms, ... |
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Honey-bees have long served as a model organism for investigating insect navigation and collective behavior: they exhibit division of labor and are an example of insect societies where direct communication between workers ... |
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How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile ... |
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Adaptive Resonance Theory (ART) neural networks model real-time prediction, search, learning, and recognition. ART networks function both as models of human cognitive information processing [1,2,3] and as neural systems for ... |
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Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi?sensor, data fusion. Single-channel Fusion ARTMAP is functionally equivalent to Fuzzy ART during unsupervised learning and to Fuzzy ... |
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Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Fusion ARTMAP generalizes the fuzzy ARTMAP architecture in order to adaptively classify multi-channel data. The ... |
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Sensors working at different times, locations, and scales, and experts with different goals, languages, and situations, may produce apparently inconsistent image labels that are reconciled by their implicit underlying ... |
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In support of the AFOSR program in Information Fusion, the CNS Technology Laboratory at Boston University is developing and applying neural models of image and signal processing, pattern learning and recognition, associative ... |
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The Sensor Exploitation Group of MIT Lincoln Laboratory incorporated an early version of the ARTMAP neural network as the recognition engine of a hierarchical system for fusion and data mining of registered geospatial ... |
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The DISCOV (DImensionless Shunting COlour Vision) system models a cascade of primate colour vision cells: retinal ganglion, thalamic single opponent, and two classes of cortical double opponents. A unified model formalism ... |
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Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and ... |
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Classifying terrain or objects may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from users with different goals and situations. Current fusion methods ... |
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The code allows for the creation, training, and testing of a Fuzzy ARTMAP neural network system. The following example datasets are also included in the zip file.
- Stripes benchmark (sparse)
- Stripes benchmark
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These MATLAB-ready .mat data files contain pixel data for the Boston remote sensing testbed. This is the same data that is provided with Classer. However, all the Classer preprocessing scripts have been run, so the mat file ... |
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