Error Correction Method for Untrained Data to Estimate Accurate Parking Vehicle Shape by Millimeter-Wave Radar with Deep Learning
نویسندگان
چکیده
We research parking scene reconstruction by a deep neural network (DNN) using millimeter-wave radar. High accuracy can be achieved for the training dataset; however, it is degraded on untrained data. It an unavoidable challenge of generalizability in machine learning. To solve this issue, we propose method to utilize model knowledge and estimate reliability results. The vehicle shape with Bezier curve applied, parameters are estimated DNN. generative model, Variational Auto Encoder (VAE) trained dataset. When low, parameter corrected stable deductive model. correction effectiveness was confirmed experimental data measured actual scenes.
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ژورنال
عنوان ژورنال: International journal of automotive engineering
سال: 2022
ISSN: ['2185-0984', '2185-0992']
DOI: https://doi.org/10.20485/jsaeijae.13.2_97