Segmentation of analogue meter readings using neural networks
| dc.contributor.author | Слюсар, Вадим Іванович | |
| dc.contributor.author | Слюсарь, Ігор Іванович | |
| dc.contributor.author | Пілюгін, В.А. | |
| dc.contributor.author | Бігун, Н. | |
| dc.contributor.author | Slyusar, V. I. | |
| dc.contributor.author | Sliusar, I. I. | |
| dc.date.accessioned | 2023-01-01T16:39:15Z | |
| dc.date.available | 2023-01-01T16:39:15Z | |
| dc.date.issued | 2022-11-25 | |
| dc.description | The report discusses options for solving the image segmentation problem of displaying digital indicators of analogue water or gas meters using neural networks. The results of a comparative analysis of the application of various implementation options for neural networks based on PSP, U-Net, and U-Net2 are presented. The Water Meters Dataset, which is freely available on the Kaggle website, was used as a dataset. In this case, the analysis was carried out by comparing various parameters of the learning process, as well as the value of the accuracy indicator on the validation sample. Its maximum value was reached at the level of 86.5% when using the PSPBlock2D neural network and 88.8% - on the light version of U-Net. | uk_UA |
| dc.identifier.uri | https://dspace.pdau.edu.ua/handle/123456789/13665 | |
| dc.subject | Neural Network | uk_UA |
| dc.subject | segmentation | uk_UA |
| dc.subject | U-Net | uk_UA |
| dc.subject | PSP | uk_UA |
| dc.title | Segmentation of analogue meter readings using neural networks | uk_UA |
| dc.type | Thesis | uk_UA |
| local.department | 3.3 Кафедра інформаційних систем та технологій | uk_UA |
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