减弱不好
发表于 2025-3-25 05:03:29
Image Analysis of Ductal Proliferative Lesions of Breast Using Architectural Features nucleus. In the present study, we obtained classification accuracy rates of 91.33%, the architectural features of breast ducts has been advanced as a useful features in the classification for distiguishing DH and DCIS. We expect that the proposed method in this paper could be used as a useful diagn
FACT
发表于 2025-3-25 10:16:12
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Breach
发表于 2025-3-25 13:02:26
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奇思怪想
发表于 2025-3-25 17:35:04
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CLAM
发表于 2025-3-25 20:03:07
A New Classifier Design with Fuzzy Functions of the data vectors as additional input variables. FCF is proposed as an alternate representation and reasoning schema to fuzzy rule base classifiers. The proposed method is evaluated by the comparison of experiments with the standard classifier methods using cross validation on test patterns.
CRATE
发表于 2025-3-26 03:44:50
Nucleus Segmentation and Recognition of Uterine Cervical Pap-Smearsd B channels. The fuzzy RBF Network is then applied to classify and identify the normal or abnormal nucleus. The result shows that the accuracy of our method is 80% overall and 66% in 5-class problem according to the Bethesda system.
观点
发表于 2025-3-26 05:46:49
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偏见
发表于 2025-3-26 09:18:17
A Study: Segmentation of Lateral Ventricles in Brain MRI Using Fuzzy C-Means Clustering with GaussiaM is able to segment lateral ventricular compartments by reducing inappropriate clustering caused by noise and inhomogeneous intensity distribution. The results demonstrate both noise insensitivity and more homogeneous clustering.
Yourself
发表于 2025-3-26 15:39:54
0302-9743 ranular Computing (RSFDGrC 2007), a part of the Joint Rough Set Symposium (JRS 2007) organized by Infobright Inc. and York University. JRS 2007 was held for the ?rst time during May 14–16, 2007 in MaRS Discovery District, Toronto, Canada. It consisted of two conferences: RSFDGrC 2007 and the Second
verdict
发表于 2025-3-26 17:24:43
Toward Rough-Granular Computingting (PBC) . The perceived concepts are expressed in natural language. We discuss the rough-granular approach to approximation of such concepts from sensory data and domain knowledge. This additional knowledge, represented by ontology of concepts, is used to make it feasible searching for featur