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The original images are first divided into several blocks and a set of visual features is extracted for each block. An array of C-RSPM (Collateral Representative Subspace Projection Modeling) models is then built that each model is based on one block from the same location in original images. Finally, the C-Value Enhanced Majority Voting (CEWMV) algorithm is developed to derive the final classification label for each testing image. To evaluate this framework, the authors compare its performance with several well-known classifiers using the benchmark data available from IICBU data repository. The results demonstrate that this framework achieves promising performance and performs significantly better than other classifiers in the comparison.<\/p>","DOI":"10.4018\/jmdem.2011040104","type":"journal-article","created":{"date-parts":[[2011,10,20]],"date-time":"2011-10-20T14:39:52Z","timestamp":1319121592000},"page":"54-70","source":"Crossref","is-referenced-by-count":10,"title":["Multimodal Information Integration and Fusion for Histology Image Classification"],"prefix":"10.4018","volume":"2","author":[{"given":"Tao","family":"Meng","sequence":"first","affiliation":[{"name":"University of Miami, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0902-0844","authenticated-orcid":true,"given":"Mei-Ling","family":"Shyu","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}]},{"given":"Lin","family":"Lin","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}]}],"member":"2432","reference":[{"key":"jmdem.2011040104-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.02.012"},{"key":"jmdem.2011040104-1","doi-asserted-by":"publisher","DOI":"10.1016\/0031-3203(82)90055-3"},{"key":"jmdem.2011040104-2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-02976-9_17"},{"key":"jmdem.2011040104-3","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2006-7-10-r100"},{"key":"jmdem.2011040104-4","doi-asserted-by":"crossref","unstructured":"Chen, S.-C., Shyu, M.-L., & Chen, M. 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