J
Jie Li
Researcher at Xidian University
Publications - 697
Citations - 15933
Jie Li is an academic researcher from Xidian University. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 54, co-authored 645 publications receiving 11695 citations. Previous affiliations of Jie Li include Zhengzhou University & University of Tsukuba.
Papers
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A Comprehensive Survey to Face Hallucination
TL;DR: This paper comprehensively surveys the development of face hallucination, including both face super-resolution and face sketch-photo synthesis techniques, and presents a comparative analysis of representative methods and promising future directions.
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Big Data Meet Green Challenges: Big Data Toward Green Applications
TL;DR: The relations between the trend of big data era and that of the new generation green revolution are discovered through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.
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ACPN: A Novel Authentication Framework with Conditional Privacy-Preservation and Non-Repudiation for VANETs
Jie Li,Huang Lu,Mohsen Guizani +2 more
TL;DR: This paper proposes a novel framework with preservation and repudiation (ACPN) for VANETs, and introduces the public-key cryptography to the pseudonym generation, which ensures legitimate third parties to achieve the non-repudiation of vehicles by obtaining vehicles' real IDs.
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A deep feature based framework for breast masses classification
TL;DR: A deep feature based framework for breast mass classification task that mainly contains a convolutional neural network (CNN) and a decision mechanism to better simulate the diagnostic procedure operated by doctors and achieved state-of-art performance.
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Channel-Wise and Spatial Feature Modulation Network for Single Image Super-Resolution
TL;DR: A channel-wise and spatial feature modulation (CSFM) network in which a series of feature modulation memory (FMM) modules are cascaded with a densely connected structure to transform shallow features to high informative features and maintain long-term information for image super-resolution.