Analysis of Deep Learning Methods in Adaptation to the Small Data Problem Solving
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-16203-9_20
Reference32 articles.
1. Albtoush, A., Fernández-Delgado, M., Cernadas, E., Barro, S.: Quick extreme learning machine for large-scale classification. Neural Comput. Appl. 34(8), 5923–5938 (2021). https://doi.org/10.1007/s00521-021-06727-8
2. Aloysius, N., Geetha, M.: A review on deep convolutional neural networks. In: 2017 International Conference on Communication and Signal Processing (ICCSP), pp. 588–592. IEEE (2017). https://doi.org/10.1109/iccsp.2017.8286426
3. Alzubaidi, L., et al.: Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J. Big Data 8(1), 1–74 (2021). https://doi.org/10.1186/s40537-021-00444-8
4. Babichev, S., Durnyak, B., Zhydetskyy, V., Pikh, I., Senkivskyy, V.: Application of optics density-based clustering algorithm using inductive methods of complex system analysis. In: 2019 IEEE 14th International Conference on Computer Sciences and Information Technologies (CSIT), vol. 1, pp. 169–172 (2019). https://doi.org/10.1109/STC-CSIT.2019.8929869
5. Chan, D., Rao, R., Huang, F., Canny, J.: T-SNE-CUDA: GPU-accelerated T-SNE and its applications to modern data. In: 2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), pp. 330–338. IEEE (2018). https://doi.org/10.1109/cahpc.2018.8645912
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach;Engineering with Computers;2024-08-21
2. An Adaptation of the Input Doubling Method for Solving Classification Tasks in Case of Small Data Processing;Procedia Computer Science;2024
3. An Approach Towards Reducing Training Time of the Input Doubling Method via Clustering for Middle-Sized Data Analysis;Procedia Computer Science;2024
4. Machine learning for predicting energy efficiency of buildings: a small data approach;Procedia Computer Science;2024
5. An Ensemble Method for the Analysis of Small Biomedical Data based on a Neural Network Without Training;Èlektronnoe modelirovanie;2023-12-10
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3