Biosensing human blood clotting factor by dual probes: Evaluation by deep LSTM networks in time series forecasting.
Sign Up to like & getrecommendations! Published in 2021 at "Biotechnology and applied biochemistry"
DOI: 10.1002/bab.2164
Abstract: Artificial intelligent of things (AIoT) has become a potential tool to be implemented in a wide range of fields and expanding with interdisciplinary sciences. On the other hand, in clinical scenario human blood clotting disease… read more here.
Keywords: lstm networks; time series; clotting factor; human blood ... See more keywords
Neurological state changes indicative of ADHD in children learned via EEG-based LSTM networks
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac4f07
Abstract: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that pervasively interferes with the lives of individuals starting in childhood. Objective. To address the subjectivity of current diagnostic approaches, many studies have been dedicated to efforts to… read more here.
Keywords: state; adhd children; based lstm; lstm networks ... See more keywords
Leveraging LSTM Networks for Attack Detection in Fog-to-Things Communications
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Communications Magazine"
DOI: 10.1109/mcom.2018.1701270
Abstract: The evolution and sophistication of cyber-attacks need resilient and evolving cybersecurity schemes. As an emerging technology, the Internet of Things (IoT) inherits cyber-attacks and threats from the IT environment despite the existence of a layered… read more here.
Keywords: leveraging lstm; detection; fog things; lstm networks ... See more keywords
Deep Multi-Kernel Convolutional LSTM Networks and an Attention-Based Mechanism for Videos
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2019.2932564
Abstract: Action recognition greatly benefits motion understanding in video analysis. Recurrent networks such as long short-term memory (LSTM) networks are a popular choice for motion-aware sequence learning tasks. Recently, a convolutional extension of LSTM was proposed,… read more here.
Keywords: convolutional lstm; based mechanism; lstm networks; lstm ... See more keywords