A more efficient CNN architecture for plankton classification

Yan Jiangpeng
Yan Jiangpeng
Cui Zuoying
Cui Zuoying

Communications in Computer and Information Science, pp. 198-208, 2017.

Cited by: 1|Bibtex|Views16|DOI:https://doi.org/10.1007/978-981-10-7305-2_18
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Other Links: dblp.uni-trier.de

Abstract:

With mass data collected by seafloor observation networks, an autonomous system which helps to annotate these pictures are in great demand. In this paper, we study the relationship between the network architecture and the classification accuracy for the Plankton Dataset collected by Oregon State University’s Hatfield Marine Science Center...More

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