J
Jeng-Shyang Pan
Researcher at Shandong University of Science and Technology
Publications - 889
Citations - 14887
Jeng-Shyang Pan is an academic researcher from Shandong University of Science and Technology. The author has contributed to research in topics: Digital watermarking & Computer science. The author has an hindex of 50, co-authored 789 publications receiving 11645 citations. Previous affiliations of Jeng-Shyang Pan include National Kaohsiung Normal University & Technical University of Ostrava.
Papers
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Book ChapterDOI
An Efficient Solution for Time-Bound Hierarchical Key Assignment Scheme
TL;DR: The security analysis is demonstrated that the scheme is secure against outside adversary and malicious user and comparisons between recently proposed two TBHKA schemes and the scheme are made to show the advantages of the scheme.
Proceedings ArticleDOI
CS-DE: Differential Evolution with Cooperative Strategy for numerical optimization
Zhenyu Meng,Jeng-Shyang Pan +1 more
TL;DR: A novel Differential Evolution variant with Cooperative Strategy (CS-DE) which can tackle the weakness of DE variant employing a single mutation strategy and can obtain an overall better performance in comparison with several well-known DE variants.
Journal ArticleDOI
An Enhancement Grade Diffusion Algorithm for Composite Event Aggregation
Book ChapterDOI
A Fully-Automated Zebra Animal Identification Approach Based on SIFT Features
TL;DR: The experimental results show that the proposed approach is superior than other existed ones in terms of identification accuracy and the automation as the approach is fully automated while the other zebra identification systems are semi-automated or manual.
Journal ArticleDOI
An advanced gradient texture feature descriptor based on phase information for infrared and visible image matching
Xiaomin Liu,Xiaomin Liu,Jun-Bao Li,Jeng-Shyang Pan,Jeng-Shyang Pan,Jeng-Shyang Pan,Shuo Wang +6 more
TL;DR: The experimental results indicate that the performance of the proposed approach to capturing the phase information between neighboring pixels with Log-Gabor filters is higher than that of other state-of-the-art algorithms.