Results 221 to 230 of about 493,391 (248)

Exact Mean Absolute Error of Baseline Predictor, MARP0

Information and Software Technology, 2016
Shepperd and MacDonell "Evaluating prediction systems in software project estimation". Information and Software Technology 54 (8), 820-827, 2012, proposed an improved measure of the effectiveness of predictors based on comparing them with random guessing.
William B. Langdon, José Javier Dolado, Federica Sarro, Mark Harman   +3 more
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Morphological filter mean-absolute-error theorem

SPIE Proceedings, 1992
The general characterization of optimal morphological filters is based on the Matheron representation for morphological filters. As conceived in its most general form, optimal- morphological-filter design involves a search over potential bases of structuring elements that can be used to form the Matheron erosion expansion.
Robert P. Loce, Edward R. Dougherty
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Morphological correlation and mean absolute error criteria

International Conference on Acoustics, Speech, and Signal Processing, 2003
The mean absolute error criterion for signal detection and matching is linked with a morphological signal correlation (a sum of minima). Several properties of this nonlinear correlation are investigated, its performance for signal detection is compared with that of the classical (sum of products) linear correlation, and its statistical form is ...
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Mean-Absolute-Error Representation and Optimization of Computational-Morphological Filters

Graphical Models and Image Processing, 1995
Abstract Computational mathematical morphology provides a framework for analysis and representation of range-preserving, finite-range operators in the context of mathematical morphology. As such, it provides a framework for statistically optimal design in the framework of a Matheron-type representation; that is, each increasing, translation-invariant
R.P. Loce, E.R. Dougherty
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Adaptive stack filtering under the mean absolute error criterion

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
An adaptive filter algorithm is developed for the class of stack filters, which is a class of nonlinear filters obeying a weak superposition property. The adaptation algorithm can be interpreted as a learning algorithm for a group of decision-making units, the decisions of which are subject to a set of constraints called the stacking constraints. Under
Jean-Hsang Lin, Thomas M. Sellke, Edward J. Coyle   +2 more
openaire   +1 more source

The mean-absolute-error criterion for quantization

ICASSP '77. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A significant property of the mean-absolute-error (MAE) criterion for optimum quantization is derived. A criterion based on output probability distributions is first formulated, and the two equations for optimum quantizer parameters based on this criterion are obtained.
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Minimum mean absolute error stack filtering with structural constraint and goals

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
A theory for the structural behavior of stack filters is developed. This theory provides a test which can determine if a given stack filter has any root signals; a method for classifying the root signal behavior of any stack filter found to have roots; and, perhaps most important, a method for designing stack filters with specific root signals or other
Moncef Gabbouj, Edward J. Coyle
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Optimal morphological restoration: The morphological filter mean-absolute-error theorem

Journal of Visual Communication and Image Representation, 1992
Morphological restoration is grounded on the Matheron representation for morphological filters, in the present context these being monotonically increasing, translation-invariant image-to-image operators. As conceived in its most general form, optimal-morphological-filter design involves a search over potential bases of structuring elements that can be
Robert P. Loce, Edward R. Dougherty
openaire   +1 more source

Optimal parallel stack filtering under the mean absolute error criterion

IEEE Transactions on Image Processing, 1994
The authors extend the configuration of stack filtering to develop a new class of stack-type filters called parallel stack filters (PSFs). As a basis for the parallel stack filtering, the block threshold decomposition (BTD) is introduced, and its properties are investigated.
Zeng, Bing, Neuvo, Yrjo
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Generalized stack filters and minimum mean absolute error estimation

1988., IEEE International Symposium on Circuits and Systems, 2003
A class of sliding window operators called generalized stack filters is developed. This class of filters, which includes all rank order filters, stack filters, and digital morphological filters, is the set of all filters possessing the threshold decomposition architecture and a consistency property called the stacking property.
J.H. Lin, E.J. Coyle
openaire   +1 more source