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We present a multiresolution classification framework with semi-supervised learning for the indirect structural health monitoring of bridges. The monitoring approach envisions a sensing system embedded into a moving vehicle traveling across the bridge of interest to measure the modal characteristics of the bridge. To enhance the reliability of the sensing system, we use a semi-supervised learning algorithm and a semi-supervised weighting algorithm within a multiresolution classificationdoi:10.1109/icassp.2013.6638291 dblp:conf/icassp/ChenCGHSRBGK13 fatcat:zq44lfm5c5bxvp2zp4tr2ml4ze