Marine Phytoplankton Recognition Using Hybrid Classification Methods

摘要：

Marine phytoplanktons are unicellular algae with avariety of shapes and ornamentation, and they are widely used asindicators of marine ecosystem changes. A dual layer and hybridclassifier is presented in this study for phytoplankton recognition.The method is based on k-NN, SVM mechanisms and uses shapeand texture information such as moments, geometric featuresand gray level co-occurrence matrix features. Each individualclassifier has its own specific input feature and decisionmechanism. The marine phytoplankton recognition experimentshows that the proposed classification method outperforms twowell-known stand-alone classifiers, k-NN and SVM.

作者: Lin Kang Yuanhao Gong Chenhui Yang Jinfei Luo Qiaoqi Luo Yahui Gao

作者单位: School of Information Science and Technology, Xiamen University Xiamen 361005, China School of Life Sciences, Xiamen University Xiamen 361005, China

会议类型: 国际会议

会议名称: The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

会议地点: 成都

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-18（万方平台首次上网日期，不代表论文的发表时间）