Device free human gesture recognition using Wi-Fi CSI: A survey
Device-free sensing of human gestures has gained tremendous research attention with the
recent advancements in wireless technologies. Channel State Information (CSI), a metric of …
recent advancements in wireless technologies. Channel State Information (CSI), a metric of …
[HTML][HTML] Towards database-free vision-based monitoring on construction sites: A deep active learning approach
In order to achieve database-free (DB-free) vision-based monitoring on construction sites,
this paper proposes a deep active learning approach that automatically evaluates the …
this paper proposes a deep active learning approach that automatically evaluates the …
Utilizing safety rule correlation for mobile scaffolds monitoring leveraging deep convolution neural networks
Falls from height (FFH) are still a leading cause of fatalities in the construction industry,
which also includes scaffolding-related accidents. Despite regular safety inspections …
which also includes scaffolding-related accidents. Despite regular safety inspections …
Deformation forecasting of a hydropower dam by hybridizing a long short‐term memory deep learning network with the coronavirus optimization algorithm
The safety operation and management of hydropower dam play a critical role in social‐
economic development and ensure people's safety in many countries; therefore, modeling …
economic development and ensure people's safety in many countries; therefore, modeling …
Cyber-physical-system-based safety monitoring for blind hoisting with the internet of things: A case study
C Zhou, H Luo, W Fang, R Wei, L Ding - Automation in construction, 2019 - Elsevier
This study proposed a cyber-physical-system-based safety monitoring system (CPS-SMS)
for blind hoisting in metro and underground constructions. Wuhan Metro's Sanyang road …
for blind hoisting in metro and underground constructions. Wuhan Metro's Sanyang road …
Convolutional long short-term memory model for recognizing construction workers' postures from wearable inertial measurement units
This paper proposes using Deep Neural Networks (DNN) models for recognizing
construction workers' postures from motion data captured by wearable Inertial Measurement …
construction workers' postures from motion data captured by wearable Inertial Measurement …
Capturing and understanding workers' activities in far‐field surveillance videos with deep action recognition and Bayesian nonparametric learning
Recording workers' activities is an important, but burdensome, management task for site
supervisors. The last decade has seen a growing trend toward vision‐based activity …
supervisors. The last decade has seen a growing trend toward vision‐based activity …
Review on application of artificial intelligence in civil engineering
Y Huang, J Fu - Computer Modeling in Engineering & Sciences, 2019 - ingentaconnect.com
In last few years, big data and deep learning technologies have been successfully applied in
various fields of civil engineering with the great progress of machine learning techniques …
various fields of civil engineering with the great progress of machine learning techniques …
A biologically-inspired hybrid deep learning approach for brain tumor classification from magnetic resonance imaging using improved gabor wavelet transform and …
SK Rajeev, MP Rajasekaran… - … Signal Processing and …, 2022 - Elsevier
Brain tumor represents the unnatural growth of cells in the brain and is identified to be one of
the deadliest cancers around the globe. The survival rate of this disease varies with the …
the deadliest cancers around the globe. The survival rate of this disease varies with the …
Deep learning-based extraction of construction procedural constraints from construction regulations
Construction procedural constraints are critical in facilitating effective construction procedure
checking in practice and for various inspection systems. Nowadays, the manual extraction of …
checking in practice and for various inspection systems. Nowadays, the manual extraction of …