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50篇 您的检索式：作者名="BOVOLO F"

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	题名	作者	年代	出处	被引量
1	A Detail-Preserving Scale- Driven Approach to Change Detection in Multitemporal SAR Images显示文摘	Bovolo F Bruzzone L	2005	IEEE Transactions on Geoscience and Remote Sensing2005，43，12：	1
2	A support vector domain method for change detection in muhitemporal images显示文摘	Bovolo F C-Valls G Bruzzone L	2010	PatternRecognition Letters2010，31，10：	1
3	A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain显示文摘	BOVOLO F BRUZZONE L		0，，01：	1
4	A hierarchical approach tochange detection in very liigh resolution SAH images for sur-veillance applications显示文摘	Bovolo F Marin C Rruzzone L	2013	1KF:E Transactions on Geoscienceaiul Remote Sensing2013，51，4：	1
5	Change detection in VHR images based on morphological attribute profiles 显示文摘	FALCO N MURA M D BOVOLO F	2013	IEEE Geoscience and Remote Sensing Letters2013，10，3：	1
6	A novel framework for the design of change-detection systems for very-high-resolution re- mote sensing images显示文摘	Bruzzone L Bovolo F	2012	Proceedings of the IEEE2012，，99：	1
7	Semisupervised One-Class Support Vector Ma- chines for Classification of Remote Sensing Data 显示文摘	MUNOZ-MARf J BOVOLO F GOMEZ-CHOVA L	2010	IEEE Transactions on Geoseience and Remote Sensing2010，48，8：	1
8	A split-based approach to unsupervised change detection in large-size multi-temporal images: application to tsunami-damage assessment显示文摘	Bovolo F Bruzzone L	2007	IEEE Transactions on Geoscience and Remote Sensing2007，45，6：	1
9	A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in Polar Domain显示文摘	Bovolo F Bruzzone L	2007	IEEE Trans on Geosci Remote Sens2007，45，3：	1
10	A theoretical framework for unsupervised change detection based on change vector analysis in the polar domain显示文摘	Bovolo F Bruzzone L	2007	IEEE Transactions on Geoscience and Remote Sensing2007，45，1：	1
11	A detail-preserving scale-drivenapproach to change detection in multitemporal SAR images 显示文摘	Bovolo F Bruzzone L	2005	IEEE Transactions on Geoscience and Remote Sensing2005，43，12：	1
12	Semisupervised One-class Support Vector Machines for Classification of Remote Sensing Data 显示文摘	MU OZ-MARI J BOVOLO F GO MEZ-CHOVA L	2010	IEEE Trans- actions on Geoscience and Remote Sensing2010，48，8：	1
13	A split-based approach to unsupervised change detection in large-size multi-temporal images: application to tsunami-damage assessment 显示文摘	BOVOLO F BRUZZONE L	2007	IEEE Transactions on Geoscience and Remote Sensing2007，45，6：	1
14	Spatio-con- textual fuzzy clustering with Markov random field model for change detection in remotely sensed images 显示文摘	SUBUDHI B N BOVOLO F GHOSH A	2014	Optics & Laser Technology2014，57，：	1
15	Auto-matic Selection of Frequency and Time Intervals forClassification of EEG Signals显示文摘	DALPONTE M BOVOLO F BRUZZONE L	2007	Electronics Letters2007，43，25：	1
16	A novel approach to unsupervised change detection based on a semisupervised SVM and a similarity measure显示文摘	F Bovolo L Bruzzone	2008	IEEE Transactions on Geoscience and Remote Sensing2008，46，7：	1
17	A Novel Technique for Subpixel Image Classification Based on Support Vector Machine显示文摘	BOVOLO F BRUZZONE L CARLIN L	2010	IEEE Transactions on Image Processing2010，19，11：	1
18	Semisupervised one-class support vector machines for classification of remote sensing data显示文摘	MUNOZ-MARI J BOVOLO F GOMEZ-CHOVA L	2010	IEEE Trans Geosci Remote Sens2010，48，8：	1
19	A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain显示文摘	BOVOLO F BRUZZONE L	2007	IEEE Transactions on Geoscience and Remote Sensing2007，45，1：	1
20	Detection of Land-cover Transitions in Multitemporal Remote Sensing Images with Active-learning-based Compound Classification显示文摘	DEMIR B BOVOLO F BRUZZONE L	2012	IEEE Transactions on Geoscience and Remote Sensing2012，50，5：	1

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