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Titlebook: Emerging Research in Computing, Information, Communication and Applications; ERCICA 2018, Volume N. R. Shetty,L. M. Patnaik,N. Nalini Conf

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11#
發(fā)表于 2025-3-23 10:42:40 | 只看該作者
https://doi.org/10.1007/978-3-642-73248-5 remember longer sequences. Multiple LSTM models with a different number of layers and sizes with different activation functions and dropout values were trained and tested for performance and we were able to achieve a test accuracy of 47% on a fairly small dataset which far exceeds the 10% accuracy
12#
發(fā)表于 2025-3-23 15:25:29 | 只看該作者
F. Boissevain,H. Wittmann,O. P. Hornstein to separate among male and female handwriting recognition compositions. The execution of the proposed framework was assessed on two databases, HWSC and TST1, inside various testing exploratory situations and acknowledged arrangement rates of up to 94.07%.
13#
發(fā)表于 2025-3-23 18:43:41 | 只看該作者
Emerging Research in Computing, Information, Communication and ApplicationsERCICA 2018, Volume
14#
發(fā)表于 2025-3-24 00:52:52 | 只看該作者
15#
發(fā)表于 2025-3-24 05:49:09 | 只看該作者
16#
發(fā)表于 2025-3-24 06:34:14 | 只看該作者
Effect of Lattice Topologies and Distance Measurements in Self-Organizing Map for Better Classificadistance measurement are implemented. This paper investigates the performance of SOM using different topologies and different distance measurements. The results obtained showed that SOM with hexagonal topology and Euclidean distance measurement outperforms other topologies and distance measurement using at any scale datasets.
17#
發(fā)表于 2025-3-24 14:45:18 | 只看該作者
18#
發(fā)表于 2025-3-24 15:40:54 | 只看該作者
19#
發(fā)表于 2025-3-24 22:29:39 | 只看該作者
20#
發(fā)表于 2025-3-25 01:24:07 | 只看該作者
Neue Entwicklungen in der Dermatologiedistance measurement are implemented. This paper investigates the performance of SOM using different topologies and different distance measurements. The results obtained showed that SOM with hexagonal topology and Euclidean distance measurement outperforms other topologies and distance measurement using at any scale datasets.
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