增强现实和机器学习的内容增强

IF 3.6 4区 地球科学 Q1 Earth and Planetary Sciences Journal of Southern Hemisphere Earth Systems Science Pub Date : 2020-10-01 DOI:10.1071/ES19046
J. Freeman
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引用次数: 4

摘要

通过将机器学习方法与增强现实显示器相结合,展示了现实世界环境的内容增强。机器学习方法和神经网络架构的进步促进了快速准确的对象和图像检测、识别和分类,并为环境预测和预测提供了机器翻译、自然语言处理和神经网络方法。这些方法使计算机具备了解释自然环境的手段。增强现实是将计算机生成的资产嵌入到现实世界环境中。在这里,我将通过开发四个示例移动应用程序来演示如何将机器学习和增强现实相结合,以创建本地化、上下文感知和以用户为中心的环境信息传递渠道。示例移动应用程序演示了增强现实内容对静态现实世界对象的增强,以提供额外的环境和上下文信息,语言翻译以促进预测信息的可访问性,以及利用临近广播神经网络的位置感知雨事件增强现实通知应用程序。
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Content enhancement with augmented reality and machine learning
Content enhancement of real-world environments is demonstrated through the combination of machine learning methods with augmented reality displays. Advances in machine learning methods and neural network architectures have facilitated fast and accurate object and image detection, recognition and classification, as well as providing machine translation, natural language processing and neural network approaches for environmental forecasting and prediction. These methods equip computers with a means of interpreting the natural environment. Augmented reality is the embedding of computer-generated assets within the real-world environment. Here I demonstrate, through the development of four sample mobile applications, how machine learning and augmented reality may be combined to create localised, context aware and user-centric environmental information delivery channels. The sample mobile applications demonstrate augmented reality content enhancement of static real-world objects to deliver additional environmental and contextual information, language translation to facilitate accessibility of forecast information and a location aware rain event augmented reality notification application that leverages a nowcasting neural network.
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来源期刊
Journal of Southern Hemisphere Earth Systems Science
Journal of Southern Hemisphere Earth Systems Science Earth and Planetary Sciences-Oceanography
CiteScore
8.10
自引率
8.30%
发文量
0
审稿时长
>12 weeks
期刊介绍: The Journal of Southern Hemisphere Earth Systems Science (JSHESS) publishes broad areas of research with a distinct emphasis on the Southern Hemisphere. The scope of the Journal encompasses the study of the mean state, variability and change of the atmosphere, oceans, and land surface, including the cryosphere, from hemispheric to regional scales. general circulation of the atmosphere and oceans, climate change and variability , climate impacts, climate modelling , past change in the climate system including palaeoclimate variability, atmospheric dynamics, synoptic meteorology, mesoscale meteorology and severe weather, tropical meteorology, observation systems, remote sensing of atmospheric, oceanic and land surface processes, weather, climate and ocean prediction, atmospheric and oceanic composition and chemistry, physical oceanography, air‐sea interactions, coastal zone processes, hydrology, cryosphere‐atmosphere interactions, land surface‐atmosphere interactions, space weather, including impacts and mitigation on technology, ionospheric, magnetospheric, auroral and space physics, data assimilation applied to the above subject areas . Authors are encouraged to contact the Editor for specific advice on whether the subject matter of a proposed submission is appropriate for the Journal of Southern Hemisphere Earth Systems Science.
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