Dorsa Mavedatnia, Lily Wang, Alex Kiss, Eric Monteiro, Vincent Lin
Health literacy of patients eligible for cochlear implants
Cochlear implants international
advances deep learning computer vision overcome many challenges inherent field autonomous intelligent vehicles improve detection accuracy efficiency edgeboard intelligent vehicles proposed optimized design edgeboard based ppyoloe model model innovatively introduces composite backbone network incorporating deep residual networks feature pyramid networks represblock structures enrich environmental perception capabilities advanced analysis sensor data incorporation efficient taskaligned head ethead ppyoloe framework marks pivotal innovation precise interpretation sensor information addressing interplay classification localization tasks high effectiveness subsequent refinement target regions detection head units significantly sharpens systems ability navigate adapt diverse driving scenarios innovative hardware design featuring customdesigned mainboard drive board specifically tailored enhance computational speed data processing capabilities intelligent vehicles furthermore optimization pospid control algorithm allows system dynamically adjust complex driving scenarios significantly enhancing vehicle safety reliability besides methodology leverages latest technologies edge computing dynamic label assignment enhancing intelligent vehicles operations seamless sensor integration custom dataset specifically designed study includes 4777 images captured intelligent vehicles variety environmental lighting conditions dataset features diverse scenarios objects pertinent autonomous driving pedestrian crossings traffic signs ensuring comprehensive evaluation models performance conducted extensive testing model dataset thoroughly assess sensor performance evaluated metrics including accuracy error rate precision recall mean average precision map f1score findings reveal model achieves remarkable accuracy rate 99113 map 549 realtime detection frame rate 192 fps within compact parameter footprint 81 mb results demonstrate superior capability ppyoloe model integrate sensor data achieving optimal balance detection accuracy computational speed compared existing algorithms