Search results for "True positive rate"

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Salient Spin Images: A Descriptor for 3D Object Recognition

2018

In the last decades a wide range of algorithms have been devoted to recognize 3D free-from objects under real conditions such as occlusions, clutters, rotation, scale and translation. Spin image is one of these algorithms known to be robust to rotation, translation, occlusions up to 70% and clutters up to 60%, but still suffer from scaling, resolution changes and it is time consuming. In this paper we present a novel approach based on spin images, called salient spin images (SSI). This method enhances spin images algorithm based on its limits. Particularly, it decreases significantly the complexity of the algorithm using DoG detector, it shows a higher performance due to the relevant locali…

Spin imageComputer sciencebusiness.industryDetectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCognitive neuroscience of visual object recognition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]01 natural sciences[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]010309 opticsRobustness (computer science)SalientComputer Science::Computer Vision and Pattern Recognition0103 physical sciences0202 electrical engineering electronic engineering information engineeringClutter020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessTrue positive rateScalingComputingMilieux_MISCELLANEOUS
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Automatische Berechnung des Milzvolumens aus Spiral-CT-Daten mit Hilfe neuronaler Netze und „Fuzzy Logik”∗

2000

PURPOSE To assess spleen segmentation and volumentry in spiral CT scans with and without pathological changes of splenic tissue. METHODS The image analysis software HYBRIKON is based on region growing, self-organized neural nets, and fuzzy-anatomic rules. The neural nets were trained with spiral CT data from 10 patients, not used in the following evaluation on spiral CT scans from 19 patients. An experienced radiologist verified the results. The true positive and false positive areas were compared in terms to the areas marked by the radiologist. The results were compared with a standard thresholding method. RESULTS The neural nets achieved a higher accuracy than the thresholding method. Cor…

Spiral CT Scansbusiness.industryRegion growingMedicineRadiology Nuclear Medicine and imagingSegmentationFalse positive rateImage analysisSpiral ctbusinessNuclear medicineTrue positive rateThresholdingRöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren
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