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Titlebook: Learning Dynamic Spatial Relations; The Case of a Knowle Andreas Bihlmaier Book 2016 Springer Fachmedien Wiesbaden 2016 machine learning te

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书目名称Learning Dynamic Spatial Relations
副标题The Case of a Knowle
编辑Andreas Bihlmaier
视频video
概述Publication in the field of technical sciences.Includes supplementary material:
图书封面Titlebook: Learning Dynamic Spatial Relations; The Case of a Knowle Andreas Bihlmaier Book 2016 Springer Fachmedien Wiesbaden 2016 machine learning te
描述.Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented..
出版日期Book 2016
关键词machine learning techniques; trained camera assistant; minimally-invasive surgery; endoscope; modular ro
版次1
doihttps://doi.org/10.1007/978-3-658-14914-7
isbn_softcover978-3-658-14913-0
isbn_ebook978-3-658-14914-7
copyrightSpringer Fachmedien Wiesbaden 2016
The information of publication is updating

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发表于 2025-3-21 23:14:43 | 显示全部楼层
Andreas Bihlmaierwidely recognized that this whole field is rapidly developing and changing in a manner beyond our imaginings of a few years ago. When confronted with conceptual revolutions of this kind, it is justifiable to have a continued on-going discourse and disputation so that there is maximum opportunity for
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Andreas Bihlmaier the effects of repeated, brief exposures on the growth of a percept, primarily of words and letters. We have shown that even in the absence of an increase in energy or stimulus adequacy (duration, luminance, contrast, visual angle, or print discriminability), well-spaced, repeated presentations not
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divergent results. Anatomical investigations, on the one hand, have revealed a rather chaotic, dense net of local and widespread interconnections between the cortical neurons. This net of interconnections lacks any apparent spatial order with respect to lengths or densities in the vertical and horiz
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