Surveillance of CSR-based TAPS Ban Violations in Vietnam to support the development of an Effective Enforcement Mechanism
Advanced Detection of E-Cigarette Ads via Image Processing
In the pursuit of heightened surveillance over e-cigarette advertising content, this research posits a timely detection strategy that leverages image processing techniques for improved regulatory oversight. The incorporation of automatic recognition systems, underpinned by advanced deep learning algorithms such as Faster R-CNN, is proposed to unearth subtle advertising strategies that typically evade standard detection barriers. This methodology endeavors to augment the management of online product representations, facilitating a systematic approach to the monitoring of e-cigarette advertising practices.
