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Confusion Matrix as Performance Measure for Corner Detectors
Journal of Advanced Research in Applied Sciences and Engineering Technology, 2022Nowadays, corner detection algorithms have been proposed by several researchers who described them contrarily, depending on their respective viewpoints to obtain the data and information as a human eye does. Basically, no researchers have come up with a technique to compare corner detectors with another’s.
null Nurul Ehsan Ramli +2 more
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Complete Control of an Observed Confusion Matrix
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018The error matrix has been adopted as a standard way to report on the thematic accuracy of any remotely sensed data product. A very usual way to perform the thematic accuracy analysis of an error matrix is by means of global indexes (e.g. overall accuracy, Kappa coefficient). But global indices do not allow for a category-wise control.
F.J. Ariza-Lopez +2 more
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Confusion Matrix Visualization
2004Using the technique of multidimensional scaling the paper demonstrates a method of visualizing a configuration of classes as it is perceived by a classifier. The methodology serves to assist the analysis of multi-class classification problems, where the final result of averaged accuracy or averaged error is not sufficient.
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Naval Target Classification Based on the Confusion Matrix
2008 IEEE Aerospace Conference, 2008In this paper, we propose an algorithm for the classification of naval targets, which is based on the fusion of the class information provided by three imaging sensors: a video camera, an infrared (IR) camera, and an airborne radar operating in spotlight Synthetic Aperture Radar (SAR) mode.
S. Giompapa +5 more
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Configurations
ABSTRACT: Confusion matrices are graphical objects used in machine learning to demonstrate the efficacy of models. They frequently take the form of brightly colored figures adorning scientific reports and technical documents. Guiding readers of these texts through an interpretation of models with their special affordances, such as diagonal lines that ...
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ABSTRACT: Confusion matrices are graphical objects used in machine learning to demonstrate the efficacy of models. They frequently take the form of brightly colored figures adorning scientific reports and technical documents. Guiding readers of these texts through an interpretation of models with their special affordances, such as diagonal lines that ...
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Analysis and Presentation of Confusion-Matrix Data
The Journal of the Acoustical Society of America, 1965As part of the work on an automatic speech recognizer, an approach has been developed to the analysis and presentation of results from confusion tests on potential vocabularies. The method depends on taking the null hypothesis that, if errors occur in a series of responses to a stimulus word.
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Using the confusion matrix for improving ensemble classifiers
2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel, 2010The code matrix enables to convert a multi class problem into an ensemble of binary classifiers. We suggest a new un-weighted framework for iteratively extending the code matrix which based on confusion matrix. The confusion matrix holds important information which is exploited by the suggested framework.
Nadav David Marom +2 more
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A Bayesian interpretation of the confusion matrix
Annals of Mathematics and Artificial Intelligence, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Proper comparison among methods using a confusion matrix
2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015An important aspect of research in the remote sensing field is to objectively compare different classifiers. This is the foundation of hundreds of research projects and in this paper we will address some raising concerns when evaluating solutions for classification of data sets with skewed class distributions.
B. P. Salmon +3 more
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Confusion Matrix-Based Building of Hierarchical Classification
2019Present an evaluation of methods for automatically building hierarchical classifiers from the analysis on the confusion matrix generated with flat classification. By defining a basic framework for that, we investigate the effects of different methods for transforming the confusion matrix, for computing the similarity between classes, and the choice of ...
Paulo Cavalin, Luiz Oliveira
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