Development of semi-supervised multiple-output soft-sensors with Co-training and tri-training MPLS and MRVM
Sign Up to like & getrecommendations! Published in 2020 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2020.103970
Abstract: Abstract Soft sensors are the most commonly used tools to estimate the hard-to-measure variables in the chemical processes and other industries, mainly due to unknown mechanism, significant measurement delay and highly unacceptable costs. However, a… read more here.
Keywords: tri training; training mpls; multiple output; training ... See more keywords
Social relationship prediction across networks using tri-training BP neural networks
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.02.057
Abstract: Abstract It is well known that the number of users is increasing rapidly in online social networks. People are linked through various types of social relationships. Detecting the type of social relationships is fundamental to… read more here.
Keywords: social relationships; network; neural networks; social networks ... See more keywords
Deep Tri-Training for Semi-Supervised Image Segmentation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3185768
Abstract: Semantic segmentation is of great value to autonomous driving and many robotic applications, while it highly depends on costly and time-consuming pixel-level annotation. To make full use of unlabeled data, this work proposes a deep… read more here.
Keywords: tri training; semi supervised; deep tri; segmentation ... See more keywords