首页|Investigators from Bhabha Atomic Research Centre Have Reported New Data on Machine Learning (Identification and Classification of Disordered Carbon Materials In a Composite Matrix Through Machine Learning Approach Integrated With Raman Mapping)
Investigators from Bhabha Atomic Research Centre Have Reported New Data on Machine Learning (Identification and Classification of Disordered Carbon Materials In a Composite Matrix Through Machine Learning Approach Integrated With Raman Mapping)
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NETL
NSTL
Elsevier
Investigators discuss new findings in Machine Learning. According to news reporting from Mumbai, India, by NewsRx journalists, research stated, “Identification and classification of different types of highly disordered carbon materials present in a polymer matrix with similar Raman spectra have been carried out using a machine learning approach. Convolutional neural network (CNN) has been used for the classification of disordered carbon materials such as graphene oxide (GO), functionalized carbon nanotube (f-CNT), carbon fiber (Cf), carbon black (CB), pyrolytic carbon (PyC), coke, and mesocarbon microbeads (MCMB).” Financial support for this research came from Bhabha Atomic Research Centre, Mumbai, India.
MumbaiIndiaAsiaCyborgsEmerging TechnologiesMachine LearningBhabha Atomic Research Centre
NETL
NSTL
Elsevier
