다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

CA : A Cancer Journal for Clinicians

We conduct an exhaustive survey of image thresholding methods, categorize them, express their formulas under a uniform notation, and finally carry their performance comparison. The thresholding methods are categorized according to the information they are exploiting, such as histogram shape, measurement space clustering, entropy, object attributes, spatial correlation, and local gray-level surface. 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images. The comparison is based on the combined performance measures. We identify the thresholding algorithms that perform uniformly better over nonde- structive testing and document image applications. © 2004 SPIE and IS&T. (DOI: 10.1117/1.1631316)

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Survey over image thresholding techniques and quantitative performance evaluation

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

Color image segmentation based on homogram thresholding and region merging

A neutrosophic approach to image segmentation based on watershed method

A neutrosophic set (Ns), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a powerful general formal framework that has been recently proposed. However, the neutrosophic set needs to be specified from a technical point of view. We apply the neutrosophic set in image domain and define some concepts and operations for image thresholding. The image G is transformed into Ns domain, which is described using three subsets T, I and F. The entropy in neutrosophic set is defined and employed to evaluate the indetermination. A new λ-mean operation is proposed to reduce the set's indetermination. Finally, the proposed method is employed to perform image thresholding. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively. Especially, it can process the "clean" images, the images with different kinds of noise and the images with multiple kinds of noise well without knowing the type of the noise, which is the most difficult task for image thresholding.

A new neutrosophic approach to image thresholding

Conventional visual and manual pavement cracking analysis approaches are very costly, time-consuming, dangerous, labor-intensive, and subjective. They possess various drawbacks such as having a hig...

Heng-Da Cheng

Papers

Color image segmentation based on homogram thresholding and region merging

A neutrosophic approach to image segmentation based on watershed method

A new neutrosophic approach to image thresholding

Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory

A novel fuzzy logic approach to contrast enhancement