Deep learning for site safety: Real-time detection of personal protective equipment
The leading causes of construction fatalities include traumatic brain injuries (resulted from
fall and electrocution) and collisions (resulted from struck by objects). As a preventive step …
fall and electrocution) and collisions (resulted from struck by objects). As a preventive step …
Learned image downscaling for upscaling using content adaptive resampler
W Sun, Z Chen - IEEE Transactions on Image Processing, 2020 - ieeexplore.ieee.org
Deep convolutional neural network based image super-resolution (SR) models have shown
superior performance in recovering the underlying high resolution (HR) images from low …
superior performance in recovering the underlying high resolution (HR) images from low …
[HTML][HTML] Deep convolutional networks for construction object detection under different visual conditions
ND Nath, AH Behzadan - Frontiers in Built Environment, 2020 - frontiersin.org
Sensing and reality capture devices are widely used in construction sites. Among different
technologies, vision-based sensors are by far the most common and ubiquitous. A large …
technologies, vision-based sensors are by far the most common and ubiquitous. A large …
Task-aware image downscaling
Image downscaling is one of the most classical problems in computer vision that aims to
preserve the visual appearance of the original image when it is resized to a smaller scale …
preserve the visual appearance of the original image when it is resized to a smaller scale …
A Survey on Intelligent Solutions for Increased Video Delivery Quality in Cloud-Edge-End Networks
The digital age has brought a significant increase in video traffic. This traffic growth, driven
by rapid internet advancements and a surge in multimedia applications, presents both …
by rapid internet advancements and a surge in multimedia applications, presents both …
A framework based on symbolic regression coupled with extended physics-informed neural networks for gray-box learning of equations of motion from data
We propose a framework and an algorithm to uncover the unknown parts of nonlinear
equations directly from data. The framework is based on eXtended Physics-Informed Neural …
equations directly from data. The framework is based on eXtended Physics-Informed Neural …
Adaptive residual networks for high-quality image restoration
Image restoration methods based on convolutional neural networks have shown great
success in the literature. However, since most of networks are not deep enough, there is still …
success in the literature. However, since most of networks are not deep enough, there is still …
[HTML][HTML] A comparative analysis of super-resolution techniques for enhancing micro-CT images of carbonate rocks
R Soltanmohammadi, SA Faroughi - Applied Computing and Geosciences, 2023 - Elsevier
High-resolution digital rock micro-CT images captured from a wide field of view are essential
for various geosystem engineering and geoscience applications. However, the resolution of …
for various geosystem engineering and geoscience applications. However, the resolution of …
[HTML][HTML] Comparing Machine Learning and Deep Learning Techniques for Text Analytics: Detecting the Severity of Hate Comments Online
Social media platforms have become an increasingly popular tool for individuals to share
their thoughts and opinions with other people. However, very often people tend to misuse …
their thoughts and opinions with other people. However, very often people tend to misuse …
[HTML][HTML] Making low-resolution satellite images reborn: a deep learning approach for super-resolution building extraction
Existing methods for building extraction from remotely sensed images strongly rely on aerial
or satellite-based images with very high resolution, which are usually limited by …
or satellite-based images with very high resolution, which are usually limited by …