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Xingchen Wang and Peng Li
With the widespread adoption of cloud computing, the face verification process often requires the client to upload the face to an untrusted cloud server to obtain the verification results. Privacy leakage issues may arise if the client?s private informat...
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Yuanzhe Yang, Zhiyi Niu, Yuying Qiu, Biao Song, Xinchang Zhang and Yuan Tian
The widespread application of multimedia technologies such as video surveillance, online meetings, and drones facilitates the acquisition of a large amount of data that may contain facial features, posing significant concerns with regard to privacy. Prot...
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Wenbin Xiang, Xuncheng Wu, Chuanchang Li, Weiwei Zhang and Feiyang Li
this study proposes a new fatigue driving detection model based on the combination of 3D convolution and attention mechanism, which can evaluate the driver?s fatigue state, reduce the accident rate and ensure the driver?s safety.
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Unai Elordi, Chiara Lunerti, Luis Unzueta, Jon Goenetxea, Nerea Aranjuelo, Alvaro Bertelsen and Ignacio Arganda-Carreras
In this paper, we tackle the problem of deploying face recognition (FR) solutions in heterogeneous Internet of Things (IoT) platforms. The main challenges are the optimal deployment of deep neural networks (DNNs) in the high variety of IoT devices (e.g.,...
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Alfredo J. Perez, Sherali Zeadally, Scott Griffith, Luis Y. Matos Garcia and Jaouad A. Mouloud
The privacy of users and information are becoming increasingly important with the growth and pervasive use of mobile devices such as wearables, mobile phones, drones, and Internet of Things (IoT) devices. Today many of these mobile devices are equipped w...
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Durkhyun Cho, Jin Han Lee and Il Hong Suh
We live in an era of privacy concerns. As smart devices such as smartphones, service robots and surveillance cameras spread, preservation of our privacy becomes one of the major concerns in our daily life. Traditionally, the problem was resolved by simpl...
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