Conference
Impact of the Pre-Processing in AI-Based Classification at Mm-Waves
| العنوان: | Impact of the Pre-Processing in AI-Based Classification at Mm-Waves |
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| المؤلفون: | Zidane, Flora, Lanteri, Jerôme, Marot, Julien, Migliaccio, Claire |
| المساهمون: | Laboratoire d'Electronique, Antennes et Télécommunications (LEAT), Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA), Institut FRESNEL (FRESNEL), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting ; https://hal.science/hal-03710922 ; IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Jul 2022, denver, United States. pp.203-204, ⟨10.1109/AP-S/USNC-URSI47032.2022.9886369⟩ ; https://ieeexplore.ieee.org/document/9886369 |
| بيانات النشر: | HAL CCSD |
| سنة النشر: | 2022 |
| المجموعة: | HAL Université Côte d'Azur |
| مصطلحات موضوعية: | Training, Fast Fourier transforms, Conferences, Millimeter wave measurements, Millimeter wave technology, Imaging, Distance measurement, [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism |
| جغرافية الموضوع: | denver, United States |
| الوصف: | International audience ; Based on various applications involving millimeter- wave (mm-wave) imaging, we highlight the importance of processing the measurements prior to their classification with Artificial Intelligence (AI) algorithms. The key point for enabling a good classification accuracy is to obtain the same structure for the training and the test datasets. Throughout the paper, we discuss a set of pre-processing methods, ranging from 2-DimensionalFast Fourier Transform (2D-FFT) with or without segmentation to 3-Dimensional Fast Fourier Transform (3D-FFT), and their influence on the final classification results. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| Relation: | hal-03710922; https://hal.science/hal-03710922 |
| DOI: | 10.1109/AP-S/USNC-URSI47032.2022.9886369 |
| الاتاحة: | https://hal.science/hal-03710922 https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9886369 |
| رقم الانضمام: | edsbas.D390AE0C |
| قاعدة البيانات: | BASE |
| DOI: | 10.1109/AP-S/USNC-URSI47032.2022.9886369 |
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