A Fast Aerial Targets Intention Recognition Method under Imbalanced Hard-Sample
ZHAO Liang
SUN Peng
ZHANG Jieyong
ZHONG Yun
YANG Fuping
Abstract：Aimed at the problem that air target group intent is often difficult to be identified rapidly under condition of imbalanced and difficult classification,an intent recognition method is proposed based on mov-ing-window estimation of the temporal convolution self-attention network model.First,the proposed model is intended to preprocess the feature data by the moving-window estimation method.Second,the flow information of multi-dimensional time series feature data is quickly extracted by the temporal convo-lution network(TCN).Finally,the self-attention mechanism is used to capture the key features from each feature datum and optimize the weights.The simulation results show that this method improves the train-ing efficiency and classification accuracy for the intent recognition of hard-sample in imbalanced samples.
Keywords：intent recognitiontemporal convolution networks(TCN)self-attentionhard-sampleim-balance sample
Publication Date：2024-02-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 76-82 )