Repo Dosen ULM

The Effect of Batch Size and Epoch on Performance of ShuffleNet-CNN Architecture for Vegetation Density Classification (Similarity Test)

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dc.contributor.author Sari, Yuslena
dc.contributor.author Arifin, Yudi Firmanul
dc.contributor.author Novitasari, Novitasari
dc.contributor.author Faisal, Mohammad Reza
dc.date.accessioned 2023-04-26T00:19:09Z
dc.date.available 2023-04-26T00:19:09Z
dc.date.issued 2022
dc.identifier.citation Yuslena Sari, Yudi Firmana Arifin, Novitasari Novitasari, Mohammad Reza Faisal (2022). The Effect of Batch Size and Epoch on Performance of ShuffleNet-CNN Architecture for Vegetation Density Classification (Similarity Test). SIET '22: Proceedings of the 7th International Conference on Sustainable Information Engineering and Technology en_US
dc.identifier.issn https://doi.org/10.1145/3568231.3568239
dc.identifier.uri https://repo-dosen.ulm.ac.id//handle/123456789/29565
dc.language.iso en en_US
dc.publisher SIET '22: Proceedings of the 7th International Conference on Sustainable Information Engineering and Technology en_US
dc.subject Similarity Test, ShuffleNet-CNN Architecture, Vegetation Density en_US
dc.title The Effect of Batch Size and Epoch on Performance of ShuffleNet-CNN Architecture for Vegetation Density Classification (Similarity Test) en_US
dc.type Other en_US


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