Sentence examples for characterization of image from inspiring English sources

To protect the structure in a diffusion process, the diffusivity parameter should be made dependent on some characterization of image structure.

Thus, the OCT field will benefit from tissue-phantom-based test methods that provide quantitative, verifiable performance measures and rigorous characterization of image quality.

Rotationally symmetric optical systems exhibit symmetric distribution of field aberrations that can be characterized in annular zones of the field [ 53], whereas for optical systems that lack any type of symmetry, e.g. the human eye, the characterization of image quality requires measurements of a larger number of field points.

Various approaches have been proposed in the literature for texture characterization of images.

This leads to a poor semantic characterization of images and hence degrades the overall retrieval performance.

The characterization of images by recurrence quantification analysis and eye structure quantification offers auxiliary image features that could not be derived by applying standard image features alone.

Therefore, this paper investigates a hybrid deep learning architecture that generates sparse, parts-based characterization of images using latent topics and is found to be compatible for large-scale image retrieval.

In this paper we discuss an efficient methodology for the image analysis and characterization of digital images containing skin lesions using Support Vector Machines and present the results of a preliminary study.

Our characterization of each image is locked within the layers of a CNN, allowing us to discover more entangled attributes (aesthetic patterns and semantic information) and to better generalize the patterns that identify a trait.

The objective of this paper is to present an efficient methodology for the characterization of dermatological images based on measurements of extracted image features using the support vector machine (SVM) algorithm.

The aim was: (1) to develop a quantitative ultrasound image analysis to characterize tissue composition in terms of intensity and structure of the ultrasound images, and (2) to use the method for characterization of ultrasound images of the supraspinatus muscle, and the vastus lateralis muscle.