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Li, Xinyu (author), He, Yuan (author), Fioranelli, F. (author), Jing, Xiaojun (author)
Human activity recognition (HAR) plays a vital role in many applications, such as surveillance, in-home monitoring, and health care. Portable radar sensor has been increasingly used in HAR systems in combination with deep learning (DL). However, it is both difficult and time-consuming to obtain a large-scale radar dataset with reliable labels...
journal article 2022
document
Li, Shaoxuan (author), Jia, Mu (author), Le Kernec, Julien (author), Yang, Shufan (author), Fioranelli, F. (author), Romain, Olivier (author)
Nowadays, health monitoring issues are increasing as the worldwide population is aging. In this paper, the radar modality is used to classify with radar signature automatically. The classic approach is to extract features from micro-Doppler signatures for classification. This data representation domain has its limitations for activities...
conference paper 2020
document
Jia, Mu (author), Li, Shaoxuan (author), Le Kernec, Julien (author), Yang, Shufan (author), Fioranelli, F. (author), Romain, Olivier (author)
As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In...
conference paper 2020
document
Li, Y. (author)
As a significant phenomenon in meteorology, fog has attracted more and more concern from the scientific community, because of its impacts on visibility in air- and road-transportation. E.g., at airports, the frequency of aircrafts taking off and landing has to be reduced during heavy fogs, because in conditions of low visibility the pilots need...
doctoral thesis 2016
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