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In this paper, a hierarchical neural network with cascading architecture is proposed and its application to classification is analyzed.
In this paper, a hierarchical neural network with cascading architecture is proposed and its application to classification is analyzed.
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Abstract. In this paper, a hierarchical neural network with cascading architec- ture is proposed and its application to classification is analyzed.
Sep 22, 2022 · The HD-CNN follows the classification strategy of coarse-to-fine classes and modular design principles (Yan et al., 2014).
Aug 23, 2012 · In this paper, a hierarchical neural network with cascading architecture is proposed and its application to classification is analyzed.
Hierarchical networks consist of a number of loosely-coupled subnets, arranged in layers. Each subnet is intended to capture specific aspects of the input data.
May 31, 2017 · We developed a hierarchical architecture based on neural networks that is simple to train. Also, we derived an inference algorithm that can efficiently infer ...
Nov 24, 2021 · We first present our proposed HGNN architecture that incorporates hierarchy among genus and species classes in neural network construction. We ...
Hierarchical Neural Networks. The architecture consists in stacked single layered neural network where each hidden layer is the input of the next layer.
In this paper, we propose a hierarchical neural network comprising of Bi-LSTMs, Dilated Convolution operation, Capsules and Conditional Random Field (CRF) to ...