As autonomous vehicles are developing and maturing the technology to implement domestic vehicles. The critical technological problem for self-driving is traffic sign detection recognition. A recognition system essential an intelligent transportation system. digital image processing techniques object extraction of features from visual objects a huge process include many conversions pre-processin...

Real-time machine learning object detection algorithms are often found within autonomous vehicle technology and depend on quality datasets. It is essential that these work correctly in everyday conditions as well under strong sun glare. Reports indicate glare one of the two most prominent environment-related reasons for crashes. However, existing datasets, such Laboratory Intelligent & Safe Aut...

Nowadays, the number of road accident in Malaysia is increasing expeditiously. One ways to reduce through development advanced driving assistance system (ADAS) by professional engineers. Several ADAS has been proposed taking into consideration delay tolerance and accuracy itself. In this work, a traffic sign recognition developed increase safety users installing inside car for driver’s awarenes...

Object detection and image recognition are some of the most significant challenging branches in field computer vision. The prosperous development unmanned driving technology has made traffic signs crucial. Affected by diverse factors such as light, presence small objects, complicated backgrounds, results traditional sign not satisfactory. To solve this problem, paper proposes two novel models, ...

Traffic sign detection is a research hotspot in advanced assisted driving systems, given the complex background, light transformation, and scale changes of traffic targets, as well problems slow result acquisition low accuracy existing methods. To solve above problems, this paper proposes method based on lightweight multiscale feature fusion network. Since network model simple has fewer paramet...