Semi-Supervised Multiresolution Classification Using Adaptive Graph Filtering With Application to Indirect Bridge Structural Health Monitoring

We present a multiresolution classification framework with semi-supervised learning on graphs with application to the indirect bridge structural health monitoring. Classification in real-world applications faces two main challenges: reliable features can be hard to extract and few labeled signals are available for training. We propose a novel classification framework to address these problems: we use a multiresolution framework to deal with nonstationarities in the signals and extract features in each localized time-frequency region and semi-supervised learning to train on both labeled and unlabeled signals. We further propose an adaptive graph filter for semi-supervised classification that allows for classifying unlabeled as well as unseen signals and for correcting mislabeled signals. We validate the proposed framework on indirect bridge structural health monitoring and show that it performs significantly better than previous approaches.

[1]  J. P. Jones,et al.  An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex. , 1987, Journal of neurophysiology.

[2]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[3]  Dorin Comaniciu,et al.  Total variation models for variable lighting face recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Jelena Kovacevic,et al.  Automated Diagnosis of Otitis Media: Vocabulary and Grammar , 2013, Int. J. Biomed. Imaging.

[6]  Sunil K. Narang,et al.  Perfect Reconstruction Two-Channel Wavelet Filter Banks for Graph Structured Data , 2011, IEEE Transactions on Signal Processing.

[7]  Jelena Kovacevic,et al.  TOWARDS AN IMAGE ANALYSIS TOOLBOX FOR HIGH-THROUGHPUT DROSOPHILA EMBRYO RNAI SCREENS , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[8]  Sebastian Thrun,et al.  Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.

[9]  Henry Leung,et al.  Classification of audio radar signals using radial basis function neural networks , 2003, IEEE Trans. Instrum. Meas..

[10]  Naoki Saito,et al.  CLASSIFICATION OF GEOPHYSICAL ACOUSTIC WAVEFORMS USING TIME-FREQUENCY ATOMS , 1996 .

[11]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[12]  R. Coifman,et al.  A general framework for adaptive regularization based on diffusion processes on graphs , 2006 .

[13]  Avrim Blum,et al.  The Bottleneck , 2021, Monopsony Capitalism.

[14]  Jelena Kovacevic,et al.  A multiresolution approach to automated classification of protein subcellular location images , 2007, BMC Bioinformatics.

[15]  Zoubin Ghahramani,et al.  Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.

[16]  Stephen Lin,et al.  An Adaptive Multiresolution Approach to Fingerprint Recognition , 2007, 2007 IEEE International Conference on Image Processing.

[17]  Vivek K Goyal,et al.  Foundations of Signal Processing , 2014 .

[18]  Yeong-Bin Yang,et al.  Use of a passing vehicle to scan the fundamental bridge frequencies: An experimental verification , 2005 .

[19]  Ronald R. Coifman,et al.  Signal processing and compression with wavelet packets , 1994 .

[20]  Zoubin Ghahramani,et al.  Learning from labeled and unlabeled data with label propagation , 2002 .

[21]  James H. Garrett,et al.  Indirect structural health monitoring in bridges: scale experiments , 2012 .

[22]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Jelena Kovacevic,et al.  An Introduction to Frames , 2008, Found. Trends Signal Process..

[24]  U. Feige,et al.  Spectral Graph Theory , 2015 .

[25]  Yeong-Bin Yang,et al.  EXTRACTING BRIDGE FREQUENCIES FROM THE DYNAMIC RESPONSE OF A PASSING VEHICLE , 2002 .

[26]  Larry Wasserman,et al.  All of Nonparametric Statistics (Springer Texts in Statistics) , 2006 .

[27]  José M. F. Moura,et al.  Adaptive graph filtering: Multiresolution classification on graphs , 2013, 2013 IEEE Global Conference on Signal and Information Processing.

[28]  Pierre Vandergheynst,et al.  Wavelets on Graphs via Spectral Graph Theory , 2009, ArXiv.

[29]  Jelena Kovacevic,et al.  Otitis media vocabulary and grammar , 2012, 2012 19th IEEE International Conference on Image Processing.

[30]  James H. Garrett,et al.  Exploring Indirect Vehicle-Bridge Interaction for Bridge SHM , 2010 .

[31]  J. Kovacevic,et al.  Life Beyond Bases: The Advent of Frames (Part II) , 2007, IEEE Signal Processing Magazine.

[32]  I. Daubechies.  Orthonormal bases of compactly supported wavelets II: variations on a theme , 1993 .

[33]  Pascal Frossard,et al.  The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains , 2012, IEEE Signal Processing Magazine.

[34]  José M. F. Moura,et al.  Discrete Signal Processing on Graphs , 2012, IEEE Transactions on Signal Processing.

[35]  Xiaojin Zhu,et al.  --1 CONTENTS , 2006 .

[36]  Adam Krzyzak,et al.  A Distribution-Free Theory of Nonparametric Regression , 2002, Springer series in statistics.

[37]  Ronald Rosenfeld,et al.  Semi-supervised learning with graphs , 2005 .

[38]  Stephen P. Boyd,et al.  Graph Implementations for Nonsmooth Convex Programs , 2008, Recent Advances in Learning and Control.

[39]  Charles R. Farrar,et al.  Structural Health Monitoring Using Statistical Pattern Recognition Techniques , 2001 .

[40]  Matthias Seeger,et al.  Learning from Labeled and Unlabeled Data , 2010, Encyclopedia of Machine Learning.

[41]  Jelena Kovacevic,et al.  Multiresolution identification of germ layer components in teratomas derived from human and nonhuman primate embryonic stem cells , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[42]  Jelena Kovacevic,et al.  Automatic identification and delineation of germ layer components in H&E stained images of teratomas derived from human and nonhuman primate embryonic stem cells , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[43]  Hae Young Noh,et al.  Damage quantification and localization algorithms for indirect SHM of bridges , 2014 .

[44]  Jelena Kovacevic,et al.  Automated colitis detection from endoscopic biopsies as a tissue screening tool in diagnostic pathology , 2012, 2012 19th IEEE International Conference on Image Processing.

[45]  James H. Garrett,et al.  Indirect structural health monitoring of a simplified laboratory-scale bridge model , 2014 .

[46]  Prashant Parikh.  A Theory of Communication , 2010 .

[47]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[48]  Ashutosh Kumar Singh,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2010 .

[49]  J. Kovacevic,et al.  Life Beyond Bases: The Advent of Frames (Part I) , 2007, IEEE Signal Processing Magazine.

[50]  R. Coifman,et al.  Diffusion Wavelets , 2004 .

[51]  M.,et al.  Statistical and Structural Approaches to Texture , 2022 .

[52]  Matti Pietikäinen,et al.  Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[53]  Stéphane Lafon,et al.  Diffusion maps , 2006 .

[54]  Christopher M. Bishop,et al.  Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .