C.-C. Jay Kuo

TL;DR: A visible and thermal drone monitoring system that integrates deep-learning-based detection and tracking modules that outperforms the performance of each individual module containing detection or tracking only is reported.

TL;DR: A new fast stochastic block matching algorithm (SBMA) is proposed which reduces matching operations to about 2% of that of the full block matching algorithms (FBMA) with only 2% increase of the sum of absolute difference (SAD) in motion compensated residuals.

TL;DR: A fast and robust camera's auto exposure (AE) technique that is robust, fast and stable even under hardware malfunction and able to adjust the control parameter automatically in the presence of erroneous exposure is proposed in this work.

TL;DR: With the proposed integrated method, watermark embedding and retrieval processes can be done very efficiently compared with existing watermarking schemes.

TL;DR: An unsupervised feature extraction approach for BIQA based on Karhunen-Loéve transform (KLT), where a normalization operation is firstly applied to the test image by calculating its mean subtracted contrast normalized (MSCN) coefficient, and generalized Gaussian distribution is employed to model the KLT coefficients distribution in different spectral components as quality relevant features.