C
C.-C. Jay Kuo
Researcher at University of Southern California
Publications - 1070
Citations - 20283
C.-C. Jay Kuo is an academic researcher from University of Southern California. The author has contributed to research in topics: Computer science & Wavelet. The author has an hindex of 59, co-authored 955 publications receiving 16671 citations. Previous affiliations of C.-C. Jay Kuo include Ningbo University & Beihang University.
Papers
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Proceedings ArticleDOI
Video image coding via multiresolution computation of motion vectors with discontinuities
Navid Haddadi,C.-C. Jay Kuo +1 more
TL;DR: A new method is developed for computation of motion vectors from a video sequence which is appropriate for motion compensated coding and can handle both discontinuities and long range motion.
Proceedings ArticleDOI
Intrusion Detector using Hidden Markov Model against Denial of Service Attack in Wireless Networks
TL;DR: The authors' simulation results shows that the proposed HMM detector is reliable and fast to detect the attack due to its dynamic property and is compared with the existing sequential detection approach in terms of the false alarm rate and optimum detection time interval.
Journal ArticleDOI
Vertebral Bone Quality Score Independently Predicts Proximal Junctional Kyphosis and/or Failure After Adult Spinal Deformity Surgery
C.-C. Jay Kuo,Mohamed A. Soliman,Alexander O. Aguirre,Nicco Ruggiero,Marissa Kruk,Asham Khan,Moleca Ghannam,Neil D. Almeida,Patrick K. Jowdy,David E. Smolar,John Pollina,Jeffrey P. Mullin +11 more
TL;DR: In this article , the authors investigated the utility of the VBQ score in predicting Proximal junctional kyphosis (PJK) and proximal jointal failure (pJF) associated with adult spinal deformity (ASD) surgery after ASD correction.
Proceedings ArticleDOI
Progressive 3D mesh coder with octree-based space partitioning
TL;DR: A progressive 3D mesh coding scheme using the octree-based space partitioning is proposed in this work, which achieves better coding efficiency than the state-of-the-art kd-tree-based codec.
Proceedings ArticleDOI
Mobile Video Processing for Visual Saliency Map Determination
TL;DR: This work proposes a three-step procedure for visual saliency map computation: 1) motion vector (MV) field filtering, 2) background extraction and 3) contrast map computation, which is supported by experimental results.