Identification of Earth’s surface objects using ensembles of convolutional neural networks.
The paper proposes an identification technique of objects on the Earth’s surface images based on combination of machine learning methods. Different variants of multi-layer convolutional neural networks and support vector machines are considered as original models. A hybrid convolutional neural netwo...
Main Authors: | Evgenii E. Marushko, Alexander A. Doudkin, Xiangtao Zheng |
---|---|
Format: | Article |
Language: | Belarusian |
Published: |
Belarusian State University
2021-08-01
|
Series: | Журнал Белорусского государственного университета: Математика, информатика |
Subjects: | |
Online Access: | https://journals.bsu.by/index.php/mathematics/article/view/3703 |
Similar Items
-
Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine
by: Zhi Liu, et al.
Published: (2021-07-01) -
Change Detection of Selective Logging in the Brazilian Amazon Using X-Band SAR Data and Pre-Trained Convolutional Neural Networks
by: Tahisa Neitzel Kuck, et al.
Published: (2021-12-01) -
SAMPLE Dataset Objects Classification Using Deep Learning Algorithms
by: M. Turcanik, et al.
Published: (2023-04-01) -
Multi-Level Alignment Network for Cross-Domain Ship Detection
by: Chujie Xu, et al.
Published: (2022-05-01) -
Neural network technology for processing of signals from technical objects control means
by: A. A. Doudkin, et al.
Published: (2019-06-01)