An Aerial Target Recognition Algorithm Based on Self-Attention and LSTM
Source abstract
Abstract
In the application of aerial target recognition, on the one hand, the recognition error produced by the single measurement of the sensor is relatively large due to the impact of noise. On the other hand, it is difficult to ap... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Infrared Target Detection Methodologies · Advanced Algorithms and Applications · Advanced Measurement and Detection Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (44)
Show source-provided references
1. A deep learning-based satellite target recognition method using radar data
2. Aircraft target classification for conventional narrow-band radar with multi-wave gates sparse echo data10.3390/rs11222700 ↗
3. Radar HRRP target recognition with deep networks10.1016/j.patcog.2016.08.012 ↗
4. GRA-TOPSIS emitter threat assessment method based on game theory
5. A survey on algorithms for automatic target recognition
6. Radar target recognition based on central moment feature and GA-BP neural network
7. Synthetic aperture radar target recognition based on KNN
8. Radar classification of indoor targets using support vector machines, IET Radar10.1049/iet-rsn.2015.0580 ↗
9. Adversarial self-supervised learning for robust SAR target recognition10.3390/rs13204158 ↗
10. Radar target recognition based on few-shot learning10.1007/s00530-021-00832-3 ↗
11. A review of recurrent neural networks: LSTM cells and network architectures10.1162/neco_a_01199 ↗
12. Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network
13. A positive-unlabeled radar false target recognition method based on frequency response features10.1109/LSP.2023.3305192 ↗
14. DeepDA: LSTM-based deep data association network for multi-targets tracking in clutter
15. An effective spam message detection model using feature engineering and Bi-LSTM
16. A novel multi-input bidirectional LSTM and HMM based approach for target recognition from multi-domain radar range profiles10.3390/electronics8050535 ↗
17. Multiview attention CNN-LSTM network for SAR automatic target recognition10.1109/JSTARS.2021.3130582 ↗
18. Attention is all you need
19. Effective text classification using BERT, MTM LSTM, and DT10.1016/j.datak.2024.102306 ↗
20. SaberNet: Self-attention based effective relation network for few-shot learning10.1016/j.patcog.2022.109024 ↗
21. Understanding self-attention mechanism via dynamical system perspective
22. Polarimetric HRRP recognition based on ConvLSTM with self-attention10.1109/JSEN.2020.3044314 ↗
23. Self-attention Bi-LSTM networks for radar signal modulation recognition10.1109/TMTT.2021.3112199 ↗
24. A GRU-based method for predicting intention of aerial targets10.1155/2021/6082242 ↗
25. Class boundary exemplar selection based incremental learning for automatic target recognition10.1109/TGRS.2020.2970076 ↗
26. Open set incremental learning for automatic target recognition10.1109/TGRS.2019.2891266 ↗
27. Incremental learning using feature labels for synthetic aperture radar automatic target recognition10.1049/rsn2.12303 ↗
28. HRRP target recognition with deep transfer learning10.1109/ACCESS.2020.2981730 ↗
29. EFTL: Complex convolutional networks with electromagnetic feature transfer learning for SAR target recognition
30. Semi-supervised deep transfer learning-based on adversarial feature learning for label limited SAR target recognition10.1109/ACCESS.2019.2948404 ↗
31. New classes inference, few-shot learning and continual learning for radar signal recognition10.1049/rsn2.12286 ↗
32. Transformer in transformer
33. Short-term orbit prediction based on LSTM neural network
34. Residual stack-aided hybrid CNN-LSTM-based automatic modulation classification for orthogonal time-frequency space system10.1109/LCOMM.2023.3328011 ↗
35. Toward the prediction level of situation awareness for electric power systems using CNN-LSTM network10.1109/TII.2020.3047607 ↗
36. Uncertain information processing method in the reliability measurement10.3901/JME.2012.08.153 ↗
37. X. Lei, “Assumption analysis and duration simulation of three-point estimate in PERT technique,” presented at the 2011 Int. Conf. Comput. Manag. (CAMAN), Wuhan, China, May 19–21, 2011.10.1109/CAMAN.2011.5778896 ↗
38. Fuzzy-probabilistic PERT10.1007/s10479-016-2315-0 ↗
39. How adding new information modifies the estimation of the mean and the variance in PERT: A maximum entropy distribution approach10.1007/s10479-018-2857-4 ↗
40. A novel MADM framework under q-Rung orthopair fuzzy bipolar soft sets10.3390/math9172163 ↗
41. Hybrid multi-attribute decision-making model based on (m, N)-soft rough sets10.3233/JIFS-182616 ↗
42. Multiattribute decision-making under Fermatean fuzzy bipolar soft framework10.1007/s41066-021-00270-6 ↗
43. Relative entropy method in target recognition with fuzzy features
44. Fuzzy hungarian MODI algorithm to solve fully fuzzy transportation problems