semi-supervised的例句大全

A kind of semi-supervised manifold learning algorithm of image recognition is presented, which is based on the Neighborhood Preserving Projections.

提出了一种基于邻域保持投影方法（Neighborhood Preserving Projections，NPP）的半监督流形学习人脸识别算法。

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The paper is about semi-supervised learning and its applications in data mining technology.

本文研究了半监督学习算法及其在数据挖掘技术中的应用。

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A semi-supervised learning system was proposed based on ART ( adaptive resonance theory).

根据自适应谐振理论提出了半监督学习自适应谐振理论系统。

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Semi-supervised learning problems play a good role in dealing with the real world problem.

半监督学习在处理现实世界中的问题时，表现出了良好的作用。

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Image Retrieval Combining Attention Model with Semi-supervised Learning

结合显著性分析和半监督学习的图像检索算法

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We propose some systemic researches about semi-supervised learning in theory, method and application.

本文从理论、方法和应用等三个层次上讨论了半监督学习问题，并提出两种半监督学习方法。

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Multiple classifiers fusion method based on semi-supervised learning

基于半监督技术的多分类器融合策略研究

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A semi-supervised learning framework of word alignment is proposed.

针对人工标记的词对齐数据较少的问题提出了一种半监督的词对齐学习框架。

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To this problem, semi-supervised learning was proposed recently and has attracted great research interest.

针对此类问题，半监督学习近来被提出并获得广泛的研究。

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Algorithm for Semi-Supervised Learning in Image Retrieval

一种用于图像检索的新型半监督学习算法

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A Semi-Supervised Learning Algorithm Based on a Hierarchical GMM

基于分层高斯混合模型的半监督学习算法

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Speaker Identification Algorithm of Semi-Supervised Learning Mechanism

半监督学习机制下的说话人辨认算法

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So that, the semi-supervised learning methods will be used for the voice emotion recognition.

基于此，本文将半监督学习方法用于语音情感识别。

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Based on the semi-supervised learning method, machine learning, semi-supervised learning for semantic annotation.

基于半监督学习方法，介绍了机器学习中半监督学习在语义标注方面的应用。

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Research and Application of Semi-Supervised Learning Algorithms Based on "Collaborative-Participatory" Computational Cognition Model

基于合作&参与计算认知模型的半监督学习算法研究与应用

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In recent years, semi-supervised learning has become a research focus in the machine learning field, Semi-supervised learning taking advantage of labeled samples and unlabeled samples to guide the learning process, leading to better learning performance.

近年来，半监督学习已经成为机器学习领域的一个研究热点。半监督学习同时利用标记样本和无标记样本来指导学习过程，从而获得更好的学习性能。

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optical flow and particle filter on affine group are incorporated in our semi-supervised learning based tracking framework.

将光流法和仿射粒子滤波分别纳入本文设计的半监督学习跟踪系统框架。

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textile image segmentation based on semi-supervised cluster and nbs color distance

基于NBS颜色距离及半监督聚类的织物图像分割

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the work in this part presents a semi-supervised approach based on expectation maximization to incorporate unlabeled bug reports to improve bug triage.

本工作设计了基于期望最大化的半监督分派方法，融合无标签bug报告，进而提高bug分派。

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Inspired by the theory of simple random walk, we propose a unified framework for semi-supervised learning, i.e. multilevel random walk ( MRW). MRW can produce numerous multi-class label propagation algorithms by constructing various component random walk models based on prior knowledge.

在简单随机游走理论的启发下，我们提出一个统一的半监督学习框架&多层随机游走，通过构建各种组件级的随机游走模型，可以产生一系列对应的多分类标签传播算法。

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