Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Luzhe Cao"'
Publikováno v:
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience, Vol 2020 (2020)
Computational Intelligence and Neuroscience, Vol 2020 (2020)
In view of the weak generalization of traditional event recognition methods, the limitation of dependence on field knowledge of expert, the longer train time of deep neural network, and the problem of gradient dispersion, the neural network joint mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b6e4215b12be22de6243327dcee0a55
https://doi.org/10.1155/2020/7090918
https://doi.org/10.1155/2020/7090918
Publikováno v:
Computer Science and Information Systems. 17:705-715
In this paper, we propose a new model to predict the age and number of suspects through the feature modeling of historical data. We discrete the case information into values of 20 dimensions. After feature selection, we use 9 machine learning algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1fa8e839be61bcaa5d496a14b6a21f85
https://doi.org/10.2298/csis200107016z
https://doi.org/10.2298/csis200107016z
Publikováno v:
Parallel Architectures, Algorithms and Programming ISBN: 9789811527661
PAAP
PAAP
With the development of public security informatization, crime prediction has become an important tool for public security organs to carry out accurate attacks and effective governance. In this paper, we propose an algorithm to predict the number of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec26897b4ee3b3bd6bada6bd876f15ca
https://doi.org/10.1007/978-981-15-2767-8_46
https://doi.org/10.1007/978-981-15-2767-8_46
Publikováno v:
IoTBDS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6d54f20f97504fe146e515ef6dd34d9
https://doi.org/10.5220/0009370002430248
https://doi.org/10.5220/0009370002430248
Publikováno v:
Journal of Physics: Conference Series. 1549:022065
Aiming at the defects that the RBM module in DBN can only re-represent information but cannot extract information features, and can only handle one-dimensional data, the DBN network is improved, and a Conv-DBN model is proposed to recognize emergenci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8fc6c95d1d5ebdd5910ba4f031aa5b6
https://doi.org/10.1088/1742-6596/1549/2/022065
https://doi.org/10.1088/1742-6596/1549/2/022065
Publikováno v:
IOP Conference Series: Materials Science and Engineering. 782:052043
Aiming at the problem of poor portability of traditional event recognition methods, the need for a large number of learning features, and the poor interpretability of recurrent neural networks in different information features about degrees of import
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da879f353fa9c6877abc1843ecc24023
https://doi.org/10.1088/1757-899x/782/5/052043
https://doi.org/10.1088/1757-899x/782/5/052043
Publikováno v:
Computer Science & Information Systems; Oct2020, Vol. 17 Issue 3, p705-715, 11p