电邮这篇文章 Identification of analog measuring instruments readings using neural networks
- 作者: Chuprinova O.1
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隶属关系:
- Санкт-Петербургский государственный университет аэрокосмического приборостроения
- 期: 编号 6 (2024)
- 页面: 98-100
- 栏目: Artificial Intelligence
- URL: https://journals.eco-vector.com/1992-4178/article/view/636246
- DOI: https://doi.org/10.22184/1992-4178.2024.237.6.98.100
- ID: 636246
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详细
The article discusses the construction of a neural network architecture for taking readings from analog instruments. The main blocks and elements used, such as convolutional networks ResNet and Path Aggregation Network, are described. The accuracy of the resulting model was assessed on a test sample using two Loss functions.
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作者简介
O. Chuprinova
Санкт-Петербургский государственный университет аэрокосмического приборостроения
编辑信件的主要联系方式.
Email: chuprinova_o@mail.ru
кафедра метрологического обеспечения инновационных технологий и промышленной безопасности, аспирант
俄罗斯联邦参考
- Disentangling Neural Architectures and Weights: A Case Study in Supervised Classification. Nicolo Colombo, Yang Gao. Department of Computer Science Royal Holloway University of London, Egham Hill, Egham TW20 0EX, UK September 14, 2020.
- V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. Fausto Milletari, Nassir Navab, Seyed-Ahmad Ahmadi.
- Zettinig O., Shah A., Hennersperger C., Eiber M., Kroll C., K΄ubler H., Maurer T., Milletari F., Rackerseder J., zu Berge C.S. et al. Multimodal image-guided prostate fusion biopsy based on automatic deformable registration. International journal of computer assisted radiology and surgery 10(12), 1997–2007 (2015).
- Milletari F., Ahmadi S.A., Kroll C., Plate A., Rozanski V., Maiostre J., Levin J., Dietrich O., Ertl-Wagner B., B΄otzel K. et al. Hough-cnn: Deep learning for segmentation of deep brain regions in mri and ultrasound. arXiv preprint arXiv:1601.07014.
- Deep Residual Learning for Image Recognition. Kaiming He Xiangyu, Zhang Shaoqing, Ren Jian Sun Microsoft Research.
- Long J., Shelhamer E., Darrell T. Fully convolutional networks for semantic segmentation // CVPR, 2015.
- Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. Bert: Pretraining of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 4171–4186, 2019.
- Noh H., Hong S., Han B. Learning deconvolution network for semantic segmentation // Proceedings of the IEEE International Conference on Computer Vision. PP. 1520–1528.
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