Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Artificial Intelligence are presented in a new report. According to news reporting originating in Fuzhou, People’s Republic of China, by NewsRx journalists, research stated, “Empowering displays with intelligent functions enables their application in intelligent image processing and intelligent interactive displays, which is the combination of future display and artificial intelligence technologies. However, existing display technologies face significant processing and transmission burdens due to their conventional hardware separation architecture, which separates memory from the processor and display module from the processing module.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China. The news reporters obtained a quote from the research from Fuzhou University, “To address these challenges, a highly integrated memory- processing-display intelligent light-emitting hardware (MPDIH) capable of information generation, memory, processing, and visualization is proposed. The MPDIH, based on an organic light-sensitive layer and activated by ultraviolet light irradiation, exhibits unique photoinhibi- tion behavior attributed to the reverse light-induced electric field formed by the directional arrangement of photo-generated excitons. This behavior enables dynamic regulation and autonomous learning during the device training process. Leveraging this phenomenon, intelligent image processing is successfully demon- strated, achieving a significant contrast improvement with a maximum enhancement of 261% compared to unprocessed raw signals. Furthermore, the memory-processing-display intelligent image processing scheme enables fashion MNIST image recognition using an artificial neural network, and achieves noticeably higher recognition accuracy (>89%) compared to the original fuzzy images (<59%).”
NETL
NSTL
Wiley