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Improving Active Learning Methods Using Spatial Information for Remote Sensing Image Classification
1. IMPROVING ACTIVE LEARNING METHODS USING SPATIAL INFORMATION IGARSS 2011 Edoardo Pasolli Univ. of Trento, Italy [email_address] Farid Melgani Univ. of Trento, Italy July 28, 2011 Devis Tuia Univ. of València, Spain Fabio Pacifici DigitalGlobe, Colorado William J. Emery Univ. of Colorado at Boulder
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7. Proposed Strategy L : Training set SV s : Support vectors SVM Training Spectral selection criterion Spatial selection criterion U ’ s : Selected samples Selection Insertion in training set U s : Sorted samples U : Learning set Nondominated sorting Labeling L ’ s : Labeled samples Human expert
8. Spectral Criterion: Margin Sampling (MS) Selection Learning (unlabeled) set in feature space f 1 f 2 f 1 Training (labeled) set in feature space f 2 SVM model f 1 f 2 Selected samples from learning (unlabeled) set in feature space selection of samples with minimum absolute values of discriminant function 0 absolute value of discriminant function : SV
9. Spatial Criterion: Distance from SVs (Sp) Selection selection of samples with maximum distance values from the closest SV : SV 0 - distance value from the closest SV f 1 Training (labeled) set in feature space f 2 SVM model Learning (unlabeled) set in spatial space Selected samples from learning (unlabeled) set in spatial space Training (labeled) set in spatial space
10. Combined Criterion (MS&Sp) determined by nondominated sorting selection of samples starting from the Pareto Front 1 front number Front 1: Pareto Front Front 2 Front 3 Front 4 Front 5 MS: absolute value of discriminant function Sp: - distance value from the closest SV
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13. Experimental Results Training set MS criterion Sp criterion MS+Sp criterion 0 absolute value of discriminant function 0 - distance value from the closest SV 1 front number
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20. IMPROVING ACTIVE LEARNING METHODS USING SPATIAL INFORMATION IGARSS 2011 Edoardo Pasolli Univ. of Trento, Italy [email_address] Farid Melgani Univ. of Trento, Italy July 28, 2011 Devis Tuia Univ. of València, Spain Fabio Pacifici DigitalGlobe, Colorado William J. Emery Univ. of Colorado at Boulder
![IMPROVING ACTIVE LEARNING METHODS USING SPATIAL INFORMATION IGARSS 2011 Edoardo Pasolli Univ. of Trento, Italy [email_address] Farid Melgani Univ. of Trento, Italy July 28, 2011 Devis Tuia Univ. of València, Spain Fabio Pacifici DigitalGlobe, Colorado William J. Emery Univ. of Colorado at Boulder](https://image.slidesharecdn.com/pasolli-improving-active-learning-methods-using-spatial-information-110728145529-phpapp02/85/Pasolli-Improving_active_learning_methods_using_spatial_information-ppt-1-320.jpg)
![Introduction ,[object Object],Pre-processing Feature extraction Classification Image/ Signal Decision Training sample collection Training sample quality/quantity Impact on accuracies Human expert](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)