@techreport{oai:ipsj.ixsq.nii.ac.jp:00218082,
 author = {Yuan, Tian and 小川, 将克 and Yuan, Tian and Masakatsu, Ogawa},
 issue = {34},
 month = {May},
 note = {送受信アンテナ間を物体が通過するとき，その物質と通過区間をリアルタイムに推定することが目的である．送受信アンテナ間を物体が通過すると，物体の物質ごとに反射や透過，回折によりマルチパス伝搬特性が異なる．CSI を用いて，1 フレームごとに機械学習により物質を推定し，推定結果の最頻値により，物質と通過区間を識別する．本稿では，アルゴリズムに使うパラメータの調整により，通過区間と予測結果への影響を検討する．, This paper focuses on real-time estimation of the material and passing duration, frame by frame when moving object passing through transmission and receiving antennas. Using the channel state information (CSI) received from Wi-Fi module, the material of moving object between transmission and receiving antennas would be identified by machine learning. Using the time-series data of CSI, we try to predict the material, frame by frame, and we show material and its passing duration between antennas can be detected using the most frequent predicted material. In this paper, by adjusting parameters in the algorithm, we made the evaluation of the passing duration and prediction by machine learning.},
 title = {Wi-Fi CSIを用いた移動物体のラベリング方法の評価},
 year = {2022}
}