Mei-Ling Shyu

TL;DR: A progressive morphological filter was developed to detect nonground LIDAR measurements and shows that the filter can remove most of the nong round points effectively.

TL;DR: A comprehensive review of historical and recent state-of-the-art approaches in visual, audio, and text processing; social network analysis; and natural language processing is presented, followed by the in-depth analysis on pivoting and groundbreaking advances in deep learning applications.

TL;DR: A novel scheme that uses robust principal component classifier in intrusion detection problems where the training data may be unsupervised and outperforms the nearest neighbor method, density-based local outliers (LOF) approach, and the outlier detection algorithm based on Canberra metric is proposed.

TL;DR: This survey conducts a comprehensive overview of the state-of-the-art research work on multimedia big data analytics, and aims to bridge the gap between multimedia challenges and big data solutions by providing the current big data frameworks, their applications in multimedia analyses, the strengths and limitations of the existing methods, and the potential future directions in multimediabig data analytics.

TL;DR: The promising experimental performance on goal/corner event detection and sports/commercials/building concepts extraction from soccer videos and TRECVID news collections demonstrates the effectiveness of the proposed framework and indicates the great potential of extending the proposed multimedia data mining framework to a wide range of different application domains.