首页|New Findings from Linyi University Describe Advances in Machine Learning (An Ada ptive Machine Learning Framework for Multi-Scenes Road Surface Weather Condition Monitoring)
New Findings from Linyi University Describe Advances in Machine Learning (An Ada ptive Machine Learning Framework for Multi-Scenes Road Surface Weather Condition Monitoring)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on artificial in telligence have been published. According to news reporting from Shandong, Peopl e's Republic of China, by NewsRx journalists, research stated, "Timely road surf ace condition (RSC) monitoring and maintenance significantly influences road saf ety." Our news editors obtained a quote from the research from Linyi University: "The current RSC relies on fixed road surveillance cameras and in-vehicle cameras. Ho wever, the fixed camera demands higher precision, while the in-vehicle camera re quires higher timeliness. To address these challenges, this paper introduces an adaptive machine learning framework for simultaneous road surface detection on b oth device types. Initially, a convolutional neural network -based differentiati on module identifies image sources. Subsequently, an adaptive algorithm switchin g mechanism leads to the development of two algorithms improved upon the real-ti me object detection algorithms. At last, extensive experiments with datasets col lected from Ontario, Canada and Iowa U.S. validate the framework."
Linyi UniversityShandongPeople's Rep ublic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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