Title:
ニューラルネットワーク分類
Document Type and Number:
Japanese Patent JP7110240
Kind Code:
B2
Abstract:
Neural network classification may be performed by inputting a training data set into each of a plurality of first neural networks, the training data set including a plurality of samples, obtaining a plurality of output value sets from the plurality of first neural networks, each output value set including a plurality of output values corresponding to one of the plurality of samples, each output value being output from a corresponding first neural network in response to the inputting of one of the samples of the training data set, inputting the plurality of output value sets into a second neural network, and training the second neural network to output an expected result corresponding to each sample in response to the inputting of a corresponding output value set.
More Like This:
Inventors:
Shoji Sakamoto
Hiroki Nakano
Hiroki Nakano
Application Number:
JP2019565479A
Publication Date:
August 01, 2022
Filing Date:
May 31, 2018
Export Citation:
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION
International Classes:
G06N3/04; G06N3/08; G06N20/20; G06T7/00; G06V10/764; G06V10/82
Domestic Patent References:
| JP10171910A |
Other References:
Yani Chen et al.,"Hippocampus segmentation through multi-view ensemble ConvNets",2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017),米国,IEEE,2017年04月18日,pp.192-196,doi: 10.1109/ISBI.2017.7950499
Masaharu Sakamoto et al.,"Multi-stage Neural Networks with Single-sided Classifiers for False Positive Reduction and its Evaluation using Lung X-ray CT Images",arXiv.org [online],arXiv:1703.00311v3,Cornell University,2017年03月,pp.1-11,[令和3年10月13日検索], インターネット:
Masaharu Sakamoto et al.,"Multi-stage Neural Networks with Single-sided Classifiers for False Positive Reduction and its Evaluation using Lung X-ray CT Images",arXiv.org [online],arXiv:1703.00311v3,Cornell University,2017年03月,pp.1-11,[令和3年10月13日検索], インターネット:
Attorney, Agent or Firm:
Tadashi Taneichi