首页|Investigators at Faculty of Sciences and Technology Discuss Findings in Machine Learning (Enhanced Co2 Leak Detection In Soil: High-fidelity Digital Colorimetry With Machine Learning and Aces Ap0)
Investigators at Faculty of Sciences and Technology Discuss Findings in Machine Learning (Enhanced Co2 Leak Detection In Soil: High-fidelity Digital Colorimetry With Machine Learning and Aces Ap0)
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 – Fresh data on Machine Learning are pre sented in a new report. According to newsreporting originating in Palembang, In donesia, by NewsRx journalists, research stated, “The importanceof effective ca rbon capture and storage (CCS) in addressing climate change issues highlights th e needfor robust CO2 leak monitoring systems. Limitations of conventional metho ds have prompted interest inalternative approaches, such as optical CO2 sensors , which offer non-invasive and continuous monitoring.”
PalembangIndonesiaAsiaCyborgsEme rging TechnologiesMachine LearningFaculty of Sciences and Technology
NETL
NSTL
