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- W4205697800 abstract "AbstractAiming at the problems of complex structure, easy loss of vector information and large number of parameters in scalar convolutional neural network, an optimized capsule network (Op-CapsNet) model for Marine fish recognition was proposed. Firstly, CNN uses convolution kernels of different sizes to extract features and retain vector information. Secondly, improve the routing algorithm and reduce the parameters. Finally, it is verified on the data set F4K. Compared with other models, the results show that the Op-CapsNet model has higher accuracy and faster convergence speed.KeywordsMarine fishesCapsule networkModelDynamic routing algorithm" @default.
- W4205697800 created "2022-01-26" @default.
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- W4205697800 date "2022-01-01" @default.
- W4205697800 modified "2023-10-17" @default.
- W4205697800 title "Research on Marine Fish Recognition Algorithm Based on Op-CapsNet" @default.
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- W4205697800 doi "https://doi.org/10.1007/978-3-030-89698-0_68" @default.
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