A review of the application of deep learning in intelligent fault diagnosis of rotating machinery
Z Zhu, Y Lei, G Qi, Y Chai, N Mazur, Y An, X Huang - Measurement, 2023 - Elsevier
With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
Deep learning based vulnerability detection: Are we there yet?
Automated detection of software vulnerabilities is a fundamental problem in software
security. Existing program analysis techniques either suffer from high false positives or false …
security. Existing program analysis techniques either suffer from high false positives or false …
[HTML][HTML] Industry 5.0 or industry 4.0 S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies
A Raja Santhi, P Muthuswamy - International Journal on Interactive Design …, 2023 - Springer
Abstract The Industrial Revolution can be termed as the transformation of traditional
industrial practices into new techniques dominated by the technologies available at that …
industrial practices into new techniques dominated by the technologies available at that …
[HTML][HTML] A novel cryptocurrency price prediction model using GRU, LSTM and bi-LSTM machine learning algorithms
MJ Hamayel, AY Owda - Ai, 2021 - mdpi.com
Cryptocurrency is a new sort of asset that has emerged as a result of the advancement of
financial technology and it has created a big opportunity for researches. Cryptocurrency …
financial technology and it has created a big opportunity for researches. Cryptocurrency …
Highly efficient fault diagnosis of rotating machinery under time-varying speeds using LSISMM and small infrared thermal images
The existing fault diagnosis methods of rotating machinery constructed with both shallow
learning and deep learning models are mostly based on vibration analysis under steady …
learning and deep learning models are mostly based on vibration analysis under steady …
[HTML][HTML] Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction
Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver
impressive performance in many clinical tasks. Large training cohorts, however, are often …
impressive performance in many clinical tasks. Large training cohorts, however, are often …
Machine learning and deep learning in smart manufacturing: The smart grid paradigm
Industry 4.0 is the new industrial revolution. By connecting every machine and activity
through network sensors to the Internet, a huge amount of data is generated. Machine …
through network sensors to the Internet, a huge amount of data is generated. Machine …
Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …
recent years and has become an important technique for scholars to study and apply. The …
A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
Highly accurate machine fault diagnosis using deep transfer learning
We develop a novel deep learning framework to achieve highly accurate machine fault
diagnosis using transfer learning to enable and accelerate the training of deep neural …
diagnosis using transfer learning to enable and accelerate the training of deep neural …