Kernel Support Vector Machines and Convolutional Neural Networks
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Jiang, Shihao; Hartley, Richard; Fernando, Basura
Description
Convolutional Neural Networks (CNN) have achieved great success in various computer vision tasks due to their strong ability in feature extraction. The trend of development of CNN architectures is to increase their depth so as to increase their feature extraction ability. Kernel Support Vector Machines (SVM), on the other hand, are known to give optimal separating surfaces by their ability to automatically select support vectors and perform classification in higher dimensional spaces. We...[Show more]
Collections | ANU Research Publications |
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Date published: | 2019 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/313279 |
Source: | 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018 |
DOI: | 10.1109/DICTA.2018.8615840 |
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Kernel_Support_Vector_Machines_and_Convolutional_Neural_Networks.pdf | 974.62 kB | Adobe PDF | Request a copy |
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