1·A new unsupervised multiresolution edge detection technique was presented, which combines the morphological filtering, pyramid data structure and fuzzy technique.
结合数学形态学、塔型数据结构及模糊技术，提出一种新的非监督多分辨率边缘检测方法。
2·An unsupervised learning approach for analysis of human motion is proposed.
提出了一种基于非监督学习的人体运动分析方法。
3·This paper proposes a new neural network model UMAN to perform unsupervised image segmentation.
本文提出了一种新的神经网络模型UMAN，以实现非监督的图象分割。
4·This paper conveys the application of genetic algorithms (GA) which are used to improve unsupervised training and thereby increase the classification accuracy of remotely sensed data.
本文将遗传算法(GA)应用于非监督训练，提高了遥感数据的分类精度。
5·As an important unsupervised pattern recognition tool clustering analysis has been used in diverse fields such as data mining, biology, computer vision, document analysis.
聚类分析作为一种重要的非监督模式识别工具，可用于多种领域，如数据挖掘、生物学、计算机视觉、文档分析等。