首页|Data on Machine Learning Detailed by Researchers at University of Shanghai for S cience and Technology (Detecting Irradiation Defects In Materials: a Machine Lea rning Approach To Analyze Helium Bubble Images)
Data on Machine Learning Detailed by Researchers at University of Shanghai for S cience and Technology (Detecting Irradiation Defects In Materials: a Machine Lea rning Approach To Analyze Helium Bubble Images)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingoriginating in Shanghai, People’s R epublic of China, by NewsRx journalists, research stated, “Additivemanufacturin g technology has received significant attention in the field of nuclear material s due to itspotential to improve the radiation resistance of materials and comp onents. In our research, we proposeto use 304 L stainless steel fabricated by S elective Laser Melting (SLM) as a replacement for traditionalcasting due to its superior performance and optimized manufacturing technique.”
ShanghaiPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesHeliumMachine LearningUniversity of Shan ghai for Science and Technology
NETL
NSTL
