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Vehicle classification in distributed sensor networks
Abstract
The task of classifying the types of moving vehicles in a distributed, wireless sensor network is investigated. Specifically, based on an extensive real world experiment, we have compiled a data set that consists of 820 MByte raw time series data, 70 MByte of preprocessed, extracted spectral feature vectors, and baseline classification results using the maximum likelihood classifier. The purpose of this paper is to detail the data collection procedure, the feature extraction and pre-processing steps, and baseline classifier development. The database is available for download at http://www.ece.wisc.edu/~sensit starting on July 2003.
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Cited by
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Zhao, Y., Zhao, J., Yang, M., Wang, T., Wang, N., Lyu, L., Niyato, D., & Lam, K.-Y. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3037194 · Cited by 456
Approaches to Multisensor Data Fusion in Target Tracking: A Survey
Smith, D., & Singh, S. (2006) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2006.183 · Cited by 379
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Wang, R., Lai, J., Zhang, Z., Li, X., Vijayakumar, P., & Karuppiah, M. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3157725 · Cited by 203
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Metadata
- Authors
- Duarte, M. F., & Hen Hu, Y.
- Venue
- Journal of Parallel and Distributed Computing
- Publisher
- Elsevier BV
- Published
- 2004-07
- Volume
- 64
- Issue
- 7
- Pages
- 826-838
- ISSN
- 0743-7315 (ISSN-L)
- OpenAlex
- W2157017541
- Cited by
- 501
- References
- 0
- FWCI
- 55.26
- Type
- journal article
- Language
- en
- Open access
- closed
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