Abstract
Data detailed on pattern recognition and artificial intelligence have been presented. According to news reporting out of Ming Chuan University by NewsRx editors, research stated, “The neglect of perception ability to the surrounding traffic conditions has always been the major cause of traffic accidents and the inattention to blind spots is the most important factor during driving. Existing solutions are facing the problems of using expensive equipment, wrong classification of the target object type, not suitable for nighttime, and incorrectly determining if the target object is in the blind zones.” The news journalists obtained a quote from the research from Ming Chuan University: “This paper aims to improve driving perception ability by developing an all-day object detection and recognition system with more accurate performance for blind zones. The proposed method uses a general-purpose camera as a single input and a two-stage deep network architecture for object detection and recognition. The proposed system is based on a two-stage cascaded network structure. At first, the style conversion process is performed to convert the daytime and nighttime images with different brightness into consistent brightness. Then the objects in the visual blind zones are detected and identified. Therefore, the accuracy of object detection can be significantly improved.”
NETL
NSTL
World Scientific