Acquisition of information using a device that is not in physical contact with the object, such as satellite or radar images.
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A novel scheme using artificial neural networks to automate the vibration monitoring method of detecting the occurrence and location of damage in offshore jacket platforms is presented. A multiple neural network system is ... |
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A modified adaptive resonance theory (mART) neural network of modular structure is proposed. The similarity function and weight resolution of the ART neural networks are modified, and the cluster merging algorithm and ... |
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The fuzzy ARTMAP has been applied to the supervised classification of multi-spectral remotely-sensed images. This method is found to be more efficient, in terms of classification accuracy, compared to the conventional ... |
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In this paper a suitable neural classification algorithm, based on the use of Adaptive Resonance Theory (ART) networks, is applied to the fusion and classification of optical and SAR urban images. ART networks provide a ... |
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Benthic macroinvertebrate communities in stream ecosystems were assessed hierarchically through two-level classification methods of unsupervised learning. Two artificial neural networks were implemented in combination. ... |
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Global or continental-scale land cover mapping with remote sensing data is limited by the spatial characteristics of satellites. Subpixel-level mapping is essential for the successful description of many land cover patterns ... |
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Neural network classifiers have been shown to provide supervised classification results that significantly improve on traditional classification algorithms such as the Bayesian (maximum likelihood [ML]) classifier. While the ... |
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Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies ... |
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In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. ... |
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A neural network recognition and tracking system is proposed for classification of radar pulses in autonomous Electronic Support Measure systems. Radar type information is considered with position-specific information from ... |
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The ARTMAP-FD neural network performs both identification (placing test patterns in classes encountered during training) and familiarity discrimination (judging whether a test pattern belongs to any of the classes ... |
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ARTMAP-FD extends fuzzy ARTMAP to perform familiarity discrimination. That is, the network learns to abstain from meaningless guesses on patterns not belonging to a class represented in the training set. ARTMAP-FD can also ... |
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For many years, the subjects of artificial intelligence, neural networks, and fuzzy logic were developed by separate intellectual communities. This was due more, perhaps, to social and institutional barriers to ... |
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A neural network model of boundary segmentation and surface representation is developed to process images containing range data gathered by a synthetic aperture radar (SAR) sensor. The boundary and surface processing are ... |
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The authors compare the performance of fuzzy ARTMAP with that of learned vector quantization and back propagation on a handwritten character recognition task. Training with fuzzy ARTMAP to a fixed criterion used many fewer ... |
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A neural network system for boundary segmentation and surface representation, inspired by a new local-circuit model of visual processing in the cerebral cortex, is used to enhance images of range data gathered by a synthetic ... |
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This application illustrates how the fuzzy ARTMAP neural network can be used to monitor environmental changes. A benchmark problem seeks to classify regions of a Landsat image into six soil and crop classes based on images ... |
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ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool ... |
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An ARTMAP neural network is used to integrate visual information and ultrasonic sensory information on a B14 mobile robot. Training samples for the neural network are acquired without human intervention. Sensory snapshots ... |
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The raw sensory input available to a mobile robot suffers from a variety of shortcomings. Sensor fusion can yield a percept more veridical than is available from any single sensor input. In this project, the fuzzy ARTMAP ... |
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ART and ARTMAP neural networks for adaptive recognition and prediction have been applied to a variety of problems, including automatic mapping from remote sensing satellite measurements, parts design retrieval at the Boeing ... |
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While most forest maps identify only the dominant vegetation class in delineated stands, individual stands are often better characterized by a mix of vegetation types. Many land management applications, including wildlife ... |
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This article describes the application of a neural network method designed to improve the efficiency of map production from remote sensing data. Specifically, the ARTMAP neural network produces vegetation maps of the Sierra ... |
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Detecting and monitoring changes in conditions at the Earth?s surface are essential for understanding human impact on the environment and for assessing the sustainability of development. In the next decade, NASA will gather ... |
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The ability to detect and monitor changes in land use is essential for assessment of the sustainability of development. In the next decade, NASA will gather high-resolution multi-spectral and multi-temporal data, which could ... |
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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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CONFIGR (CONtour FIgure and GRound) is a model that performs long-range contour completion on large-scale images. CONFIGR accomplishes this through a mechanism that fills-in both figure and ground via complementary process. ... |
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Self-Supervised ARTMAP learns about novel features from unlabeled patterns without destroying
partial knowledge previously acquired from labeled ... |
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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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