English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Keyword: Android fatigue detection, face detection, AdaBoost Abstract. Fatigue driving, a hot issue in the field of transportation research, has become a worldwide problem which always leads to traffic accident. Existing detection method always based on costly hardware platform sensors. By developing an android APP using image processing algorithm, we can lower the costs and enable convenient detection. Generally, face detection is a key step in fatigue drive detection. However, correct result can't be required by Android system detection API, especially in side face detection or strong light condition. A smart-phone based algorithm is presented in this paper to deal with side face situation and detection under strong light. Specially, the algorithm is based on a number of AdaBoost classifier that can distinguish different poses, and it exploits the color skin model with illumination compensation to increase detection quality.

Multi-pose Face Detection under Strong Light Condition for Android Driver Fatigue detection System