bayesian probability framework
基本解釋
- [計(jì)算機(jī)科學(xué)技術(shù)]貝葉斯概率框架
英漢例句
- Each probability items in the Bayesian framework have the specific meanings.
該框架下每個(gè)概率項(xiàng)都有其具體的含義。 - For a foggy input image, there is a clear image correspondingly. The Bayesian framework is established using the maximum probability of the corresponding clear image appearing for a given foggy image.
對(duì)于輸入的一幅有霧圖像,會(huì)存在一幅清新圖像與之相對(duì)應(yīng),我們就是要求清新圖像在有霧圖像已知情況下出現(xiàn)的概率最大,為此利用圖像的統(tǒng)計(jì)模型建立了貝葉斯框架。
雙語例句
專業(yè)釋義
- 貝葉斯概率框架
Bayesian probability framework is a theory to transfer a priori probability to posterior probability. This thesis provides a formal Bayesian framework for image classification problems, which maps the low-level image features to the intrinsic high-level semantics.
貝葉斯概率框架是一種將先驗(yàn)概率轉(zhuǎn)化為后驗(yàn)概率的理論框架,通過形式化的圖像分類概率框架可以將低級(jí)圖像特征映射到已有的高層語義。