[HTML][HTML] Comparative analysis of human operators and advanced technologies in the visual inspection of aero engine blades
J Aust, D Pons - Applied Sciences, 2022 - mdpi.com
Background—Aircraft inspection is crucial for safe flight operations and is predominantly
performed by human operators, who are unreliable, inconsistent, subjective, and prone to …
performed by human operators, who are unreliable, inconsistent, subjective, and prone to …
Evaluation of convolutional neural networks' hyperparameters with transfer learning to determine sorting of ripe medjool dates
BD Pérez-Pérez, JP Garcia Vazquez… - Agriculture, 2021 - mdpi.com
Convolutional neural networks (CNNs) have proven their efficiency in various applications in
agriculture. In crops such as date, they have been mainly used in the identification and …
agriculture. In crops such as date, they have been mainly used in the identification and …
Atmospheric turbulence study with deep machine learning of intensity scintillation patterns
AM Vorontsov, MA Vorontsov, GA Filimonov… - Applied Sciences, 2020 - mdpi.com
Featured Application Atmospheric remote sensing, directed energy, free-space laser
communication, adaptive optics, lidars, active imaging, optical surveillance. Abstract A new …
communication, adaptive optics, lidars, active imaging, optical surveillance. Abstract A new …
[PDF][PDF] Virtual reality in fluid power education: Impact on students' perceived learning experience and engagement
The significance of practical experience and visualization in the fluid power discipline, highly
tied to students' success, requires integrating immersive pedagogical tools for enhanced …
tied to students' success, requires integrating immersive pedagogical tools for enhanced …
Compression helps deep learning in image classification
EH Yang, H Amer, Y Jiang - Entropy, 2021 - mdpi.com
The impact of JPEG compression on deep learning (DL) in image classification is revisited.
Given an underlying deep neural network (DNN) pre-trained with pristine ImageNet images …
Given an underlying deep neural network (DNN) pre-trained with pristine ImageNet images …
Assessing changes in mountain treeline ecotones over 30 years using CNNs and historical aerial images
Historical black-and-white (B&W) aerial images have been recognized as an important
source of information for assessing vegetation dynamics. However, the use of these images …
source of information for assessing vegetation dynamics. However, the use of these images …
Automatic, multiview, coplanar extraction for CityGML building model texture mapping
H He, J Yu, P Cheng, Y Wang, Y Zhu, T Lin, G Dai - Remote Sensing, 2021 - mdpi.com
Most 3D CityGML building models in street-view maps (eg, Google, Baidu) lack texture
information, which is generally used to reconstruct real-scene 3D models by …
information, which is generally used to reconstruct real-scene 3D models by …
Decoders configurations based on Unet family and feature pyramid network for COVID-19 segmentation on CT images
Abstract Coronavirus Disease 2019 (COVID-19) pandemic has been ferociously destroying
global health and economics. According to World Health Organisation (WHO), until May …
global health and economics. According to World Health Organisation (WHO), until May …
Virtual underwater datasets for autonomous inspections
Underwater Vehicles have become more sophisticated, driven by the off-shore sector and
the scientific community's rapid advancements in underwater operations. Notably, many …
the scientific community's rapid advancements in underwater operations. Notably, many …
Comparing interpretation of high-resolution aerial imagery by humans and artificial intelligence to detect an invasive tree species
Timely, accurate maps of invasive plant species are critical for making appropriate
management decisions to eliminate emerging target populations or contain infestations …
management decisions to eliminate emerging target populations or contain infestations …