为遥感图像解析的智能教学系统1
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附件1：外文资料翻译译文 为遥感图像解析的智能教学系统 摘要 遥感技术在军事行动中扮演着举足轻重的角色。在允许武力的情况下,卫星和航空器的摄影功能从安全隐秘的距离来估测位置方面有很大作用。 然而，有效执行遥感摄影的功能也是一项综合的科学。复杂的高视觉领域的知识,例如遥感领域知识,这些都不是从书本上可以学的到的.对一个研究者来说,要想精通,需要投入大量的时间经过专家训练才行。 本文概述一个为美国航空航天局建造的智能教学系统。这个软件的目的是提供地理科学原理教育的一对一的遥感指导。智能教学系统直接和美国航空航天局Image2000 图象加工软件集成, 实际终端环境由研究者演示真实生活任务。另外, 美国航空航天局Image2000 和智能教学系统为学生提供动态, 有效的实践教育经验。它监测和估计学生的行为, 提供直接反馈和上下文指引和挑战。分开的传作工具为由非专业人士开发的智能教学系统提供新的指导。因而, 指导者就可以有准备地对遥感兴趣强的部分作出交互的合适的指导。关于军事应用, 可以构想应用指南来广泛布署说明任务: 图像增强, 对象分类, 目标辨别, 损失情况估计, 天气预报等。指导者可以集中于一个具体地理位置。 本文概述我们研究的遥感智能教学系统, 它的一般框架, 模拟学生和专家的知识的人工智能技术, 以及它在地球科学领域的应用。 关于作者 Aaron M. Bell在软件开发上有高的地位，对引用人工智能技术解决地球科学问题投入了很大的兴趣。Stottler Henke当前是一个卫星图像解析的智能教育系统项目负责人. 附件2：外文原文（复印件） An Intelligent Tutoring System for Remote Sensing and Image Interpretation ABSTRACT Remote sensing technology is playing an increasingly central role in military operations. The interpretation of satellite and aircraft photography has great utility in allowing forces to assess a situation from a secure, stealthy distance. However, performing effective interpretations of remote sensing photography is a complex science. Knowledge of a complex, highly-visual domain, such as that of remote sensing, cannot be learned from manuals. For an analyst to become proficient requires a large investment of training time from an expert. Our paper describes an Intelligent Tutoring System (ITS) being built for NASA. The goal of this software is to provide the benefits of a one-on-one remote sensing instructor to teach Earth Science principles. The ITS integrates directly with the NASA Image2000 image processing software, the actual end environment in which researchers perform real-life tasks. Together, NASA Image2000 and the ITS provide students with a dynamic, hands-on educational experience that is cost-effective. It monitors and assesses the student's actions, provides immediate feedback as well as contextual guidance and challenges. A separate authoring tool allows new tutorials for the ITS to be developed by non-programmers. Thus, instructors can readily produce interactive, adaptive tutorials for an area of remote sensing interest. With regard to military application, tutorials can be constructed to teach the wide array of interpretation tasks: image enhancement, object classification, target discrimination, damage assessment, weather prediction, etc. The tutorials can focus on a specific geographical location. This paper outlines our research of a remote sensing ITS system, its general framework, the artificial intelligence technologies it employs to model the knowledge of the student and the expert, and its application to the Earth Science domain. |