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Machine learning and interpretation in neuroimaging[electronic resource] :International Workshop, MLINI 2011, held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised selected and invited contributions /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.31
書名/作者:	Machine learning and interpretation in neuroimaging : International Workshop, MLINI 2011, held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised selected and invited contributions // edited by Georg Langs ... [et al.].
其他題名:	MLINI 2011
其他作者:	Langs, Georg.
團體作者:	Clark Conference
出版者:	Berlin, Heidelberg : : Springer Berlin Heidelberg :, 2012.
面頁冊數:	263 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Machine learning
標題:	Artificial intelligence - Congresses. - Medical applications
標題:	Brain - Congresses. - Imaging
標題:	Computer Science.
標題:	Computer Imaging, Vision, Pattern Recognition and Graphics.
標題:	Pattern Recognition.
標題:	Data Mining and Knowledge Discovery.
標題:	Probability and Statistics in Computer Science.
標題:	Image Processing and Computer Vision.
標題:	Computer Applications.
ISBN:	9783642347139 (electronic bk.)
ISBN:	9783642347122 (paper)
摘要、提要註:	Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.
電子資源:	http://dx.doi.org/10.1007/978-3-642-34713-9

Machine learning and interpretation in neuroimaging[electronic resource] :International Workshop, MLINI 2011, held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised selected and invited contributions /
Machine learning and interpretation in neuroimagingInternational Workshop, MLINI 2011, held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised selected and invited contributions /[electronic resource] :MLINI 2011edited by Georg Langs ... [et al.]. - Berlin, Heidelberg :Springer Berlin Heidelberg :2012. - 263 p. :ill., digital ;24 cm. - Lecture notes in computer science,0302-9743. - Lecture notes in computer science..

Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.

ISBN: 9783642347139 (electronic bk.)Subjects--Topical Terms:

135653
Machine learning

LC Class. No.: Q325.5 / .M55 2011

Dewey Class. No.: 006.31

Machine learning and interpretation in neuroimaging[electronic resource] :International Workshop, MLINI 2011, held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised selected and invited contributions /
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