Xiaochen Chen

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Face information processing relies on the quality of data resource. From the data modality point of view, a face database can be 2D or 3D, and static or dynamic. From the task point of view, the data can be used for research of computer based automatic face recognition, face expression recognition, face detection, or cognitive and psychological(More)
3D facial range models can be created by static range scanners or real-time dynamic 3D imaging systems. One of the major obstacles for analyzing such data is lack of correspondences of features (or vertices) due to the variable number of vertices across individual models or 3D model sequences. In this paper, we present an effective approach to automatically(More)
DNSSEC can provide a strong countermeasure to DNS Cache Poisoning Attacks, however, DNSSEC can't be actually deployed in a short time, it is still impossible to avoid poisoning attacks thoroughly, a majority of DNS servers are still hreatened from the poisoning attacks. This attack is used in conjunction with web spoofing, it can change Web URL, lead(More)
We present the development and performance evaluation of wearable passive UHF RFID tags based on slotted patch antennas that are electromagnetically optimized for operation in the close proximity of the human body. The antennas are manufactured from an electro-textile material on a light-weight textile substrate. The required patch-toground interconnections(More)
This paper provides a viable solution to tackle Kanminsky's DNS cache poisoning attack. By analyzing DNS's resolution methods and the principle of the cache poisoning attack, the concept of cache file and hosts file is introduced in this paper. The purpose of using hosts file is to reduce the impact of DNS cache poisoning attack. By using a DNS-white-list(More)
In this paper, we use the house price data ranging from January 2004 to October 2016 to predict the average house price of November and December in 2016 for each district in Beijing, Shanghai, Guangzhou and Shenzhen. We apply Autoregressive Integrated Moving Average model to generate the baseline while LSTM networks to build prediction model. These(More)
Recently there has been a lot of interest in geometrically motivated approaches dealing with data in high dimensional spaces. We consider the case where data is sampled from a low dimensional manifold which is embedded in high dimensional Euclidean space. In this paper, we propose a novel unsupervised linear subspace learning algorithm called Local and(More)