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Typically, the morphology of wear particles is evaluated qualitatively based on microscopy observations. This procedure relies upon the experts\u2019 knowledge and, thus, is not always objective and cheap. With the rapid development of computer image processing technology, neural network based on traditional gradient training algorithm can be used to recognize them. However, the feedforward neural network based on traditional gradient training algorithms for image segmentation creates many issues, such as needing multiple iterations to converge and easy fall into local minimum, which restrict its development heavily. Recently, extreme learning machine (ELM) for single-hidden-layer feedforward neural networks (SLFN) has been attracting attentions for its faster learning speed and better generalization performance than those of traditional gradient-based learning algorithms. In this paper, we propose to employ ELM for ferrography wear particles image recognition. We extract the shape features, color features, and texture features of five typical kinds of wear particles as the input of the ELM classifier and set five types of wear particles as the output of the ELM classifier. Therefore, the novel ferrography wear particle classifier is founded based on ELM.<\/jats:p>","DOI":"10.1155\/2017\/3451358","type":"journal-article","created":{"date-parts":[[2017,3,21]],"date-time":"2017-03-21T18:04:26Z","timestamp":1490119466000},"page":"1-6","source":"Crossref","is-referenced-by-count":19,"title":["Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0697-7037","authenticated-orcid":true,"given":"Qiong","family":"Li","sequence":"first","affiliation":[{"name":"College of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin 300457, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tingting","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin 300457, 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