نتایج جستجو برای: attributive retraining

تعداد نتایج: 3092  

Journal: :Otolaryngology–Head and Neck Surgery 2011

Journal: :The Proceedings of the Annual Convention of the Japanese Psychological Association 2018

Journal: :Archives of Clinical Neuropsychology 2000

Journal: :International Journal of Economics and Business Administration 2019

Jahangir Haghani, Majid Asadi-Shekaari, Maryam Alsadat Hashemipour, Molok Torabi, Parviz Amini, Simin Esmaeli,

Introduction: Cone beam computed tomography (CBCT) is a new method that is able to provide three-dimensional images in radiology and is useful for dentomaxillofacial imaging. This study aimed to investigate the cases administrated CBCT by dentists of Kerman (2015 year). Methods: This cross-sectional study was conducted on dentists in Kerman. The data were gathered using standard research q...

Journal: :زبان شناسی و گویش های خراسان 0
آرزو نجفیان بلقیس روشن زهرا قیراطی

1- introduction the literature review of persian suffixes show that “-i, -in, -ineh, -gan, -ganeh, -aneh, and -iyeh/yeh” are attributive suffixes. linguistic evidences show that once these suffixes are added to a word, in addition to the central senses of “related to” and “attributed to”, they add peripheral sense such as possession, similarity, possibility, obligation, origin, direction, goal,...

2001
Christopher Ware Joe F. Chicharo Tadeusz A. Wysocki

In this paper we investigate the performance of common capture models in terms of the fairness properties they reflect across contenting hidden connections. We propose a new capture model, Message Retraining,as a means of providing an accurate description of experimental data. Using two fairness indices we undertake a quantitative study of the accuracy with which each capture model is able to r...

2001
Qiangfu Zhao

In machine learning, symbolic approaches usually yield comprehensible results without free parameters for further (incremental) retraining. On the other hand, non-symbolic (connectionist or neural network based) approaches usually yield black-boxes which are diicult to understand and reuse. The goal of this study is to propose a machine learner that is both incrementally retrainable and compreh...

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