Clustering and semi-supervised classification with application to driver distraction detection

• Main Author: Liu, Tianchi
• Other Authors: Huang Guangbin
• Format: Theses and Dissertations
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition; DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• Online Access: https://hdl.handle.net/10356/89229; http://hdl.handle.net/10220/46179
• Institution: Nanyang Technological University

Clustering and Semi-Supervised Classification (SSC) algorithms can make use of unlabeled training data and thus have the potential to alleviate labeling costs. For example, Extreme Learning Machine (ELM) was recently extended to semi-supervised learning and clustering with promising performance. Mea...