نتایج جستجو برای: confidence based assessment

تعداد نتایج: 3468392  

پایان نامه :دانشگاه آزاد اسلامی - دانشگاه آزاد اسلامی واحد تهران مرکزی - دانشکده زبانهای خارجی 1390

writing as a productive skill requires practice in the basic sub-skills of vocabulary and grammar. in fact, grammar has been viewed as the core of programs in writing classes to help the students put the elements of sentence together and combine sentences of specific lengths to come up with an error-free work of art. conceptualizing l2 writing in this way introduces writing as a product and enc...

Journal: :Cognitive Research: Principles and Implications 2021

Journal: :Electronic Journal of Statistics 2018

Journal: :Lecture Notes in Computer Science 2021

Generating confidence calibrated outputs is of utmost importance for the applications deep neural networks in safety-critical decision-making systems. The output a network probability distribution where scores are estimated confidences input belonging to corresponding classes, and hence they represent complete estimate likelihood relative all classes. In this paper, we propose novel form label ...

Journal: :IEEE Access 2021

Unsupervised domain adaptation aims to align the distributions of data in source and target domains, as well assign labels domain. In this paper, we propose a new method named Domain Adaptation based on Pseudo-Label Confidence (UDA-PLC). Concretely, UDA-PLC first learns feature representation by projecting domains into latent subspace. subspace, distribution two are aligned discriminability fea...

2012
Kim Lowell Alex Held Tony Milne Anthea Mitchell Ian Tapley Peter Caccetta Eric Lehmann Zheng-shu Zhou

Areal sample units are explored as an alternative to conventional point-based samples for map accuracy assessment. Three analyses are examined: confidence limits on estimates of the total amount of each landcover, regression of map data versus reference data, and a two-part confusion matrix approach. It is concluded that areal sample units provide some advantages compared to point-based samples...

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