Challenges and opportunities of deep learning-based process fault detection and diagnosis: a review

J Yu, Y Zhang - Neural Computing and Applications, 2023 - Springer
Process fault detection and diagnosis (FDD) is a predominant task to ensure product quality
and process reliability in modern industrial systems. Those traditional FDD techniques are …

A review of critical fire event library for buildings and safety framework for smart firefighting

AA Khan, MA Khan, K Leung, X Huang, M Luo… - International Journal of …, 2022 - Elsevier
While occupants are evacuating from the fire scene, firefighters are entering life-threatening
environments, exposed to hot and toxic fire smoke and risks of structural failures or …

Predicting transient building fire based on external smoke images and deep learning

Z Wang, T Zhang, X Wu, X Huang - Journal of Building Engineering, 2022 - Elsevier
A real-time evaluation of fire severity inside a building could facilitate decision-making in
firefighting and rescue operations. This work explores the real-time prediction of transient …

To ensure the safety of storage: Enhancing accuracy of fire detection in warehouses with deep learning models

Q Zhang, Y Tian, J Chen, X Zhang, Z Qi - Process Safety and …, 2024 - Elsevier
Warehouses are important places with storage functions in process units, containing many
flammable and explosive materials. Nevertheless, fire protection systems often fail to provide …

Unsupervised haze removal for aerial imagery based on asymmetric contrastive cyclegan

X He, W Ji, J Xie - IEEE Access, 2022 - ieeexplore.ieee.org
Aerial image dehazing is an important preprocessing step, since haze extremely degrades
the imaging quality and affects subsequent the applications of aerial imagery. Most current …

Smart tunnel fire safety management by sensor network and artificial intelligence

X Huang, X Wu, X Zhang… - … artificial intelligence in …, 2022 - api.taylorfrancis.com
Tunnels have played an essential role in modern transportation systems since the mid-20th
century, owing to their high utility and flexibility in mountainous areas and their effectiveness …

UAV-Rain1k: A Benchmark for Raindrop Removal from UAV Aerial Imagery

W Chang, H Chen, X He, X Chen… - Proceedings of the …, 2024 - openaccess.thecvf.com
Raindrops adhering to the lens of UAVs can obstruct visibility of the background scene and
degrade image quality. Despite recent progress in image deraining methods and datasets …

Automatic estimation of post-fire compressive strength reduction of masonry structures using deep convolutional neural network

K Hacıefendioğlu, AF Genc, S Nayır, S Ayas… - Fire Technology, 2022 - Springer
A deep learning-based image processing study was carried out to predict the post-fire safety
of historical masonry structures. For this purpose, andesite stone and lime-based mortar …

Multi-stages de-smoking model based on CycleGAN for surgical de-smoking

X Su, Q Wu - International Journal of Machine Learning and …, 2023 - Springer
Smoke generated during laparoscopic surgery blocks the doctor's sight and degrades the
quality of the images severely; thus, surgical de-smoking is a crucial task during …

Special Issue on “Smart Systems in Fire Engineering”

MZ Naser, C Lautenberger, E Kuligowski - Fire Technology, 2021 - Springer
With the rise of transformative technologies: such as artificial intelligence (AI), Internet-of-
Things (IoT), robotics, sensors etc., the field of fire engineering and safety is embracing a …