Abstract
In this chapter, we introduce the general framework of the tree-based convolutional neural network (TBCNN). We first present the design philosophy and the general formula of TBCNN. Then we introduce several applications of TBCNN that will be analyzed in this book. We also highlight the technical difficulties of designing TBCNN in different scenarios, which will be addressed in future chapters.
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Notes
- 1.
\(n_c\) could also also be thought of as the number of convolution kernels, each kernel outputing one dimensional feature.
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Mou, L., Jin, Z. (2018). General Framework of Tree-Based Convolutional Neural Networks (TBCNNs). In: Tree-Based Convolutional Neural Networks. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-13-1870-2_3
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DOI: https://doi.org/10.1007/978-981-13-1870-2_3
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1869-6
Online ISBN: 978-981-13-1870-2
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