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Experiments are conducted with the sparse representation based algorithm and Support Vector Machine (SVM) classifiers on 25 object categories selected from the Caltech101 dataset. Experimental results show that without the time-consuming parameter optimization, the sparse representation based algorithm achieves comparable performance with SVM. The experiments also demonstrate that the algorithm is robust to a certain degree of background clutter and intra-class variations with the bag-of-visual-words representations. The sparse representation based algorithm can also be applied to generic image classification task when the appropriate image feature is used.<\/p>","DOI":"10.4018\/jssci.2011010101","type":"journal-article","created":{"date-parts":[[2011,10,19]],"date-time":"2011-10-19T12:48:56Z","timestamp":1319028536000},"page":"1-15","source":"Crossref","is-referenced-by-count":2,"title":["Sparse Based Image Classification With Bag-of-Visual-Words Representations"],"prefix":"10.4018","volume":"3","author":[{"given":"Yuanyuan","family":"Zuo","sequence":"first","affiliation":[{"name":"Tsinghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jssci.2011010101-0","unstructured":"Berg, E., & Friedlander, M. (2007). SPGL1: A solver for large-scale sparse reconstruction. 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