CFC-GAN: Forecasting road surface crack using forecasted crack generative adversarial network

A Sekar, V Perumal - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Forecasting the road surface crack images with given present crack images is an important
task to assist the road survivors in planning for their next lay down of road with the required …

Automatic quantification of concrete cracks via multistage image filtration and trajectory-based local binarization

TT Yalew, KS Kim - Journal of Building Engineering, 2023 - Elsevier
Ensuring the structural integrity of civil infrastructure and maintaining public safety
necessitates accurate and reliable periodic inspection of cracks on concrete surfaces. Image …

Image Recognition of Pavement Cracks in Autonomous Driving Scenarios Based on Deep Learning

Q Liu, Z Liu - 2024 5th International Conference on Computer …, 2024 - ieeexplore.ieee.org
Pavement cracking represents the predominant form of defect encountered within
autonomous driving environments. With the advancement of deep learning technologies, an …

Hybrid modeling based on integrating simulation and operational data to improve indoor air temperature predictions, a controlled variable in digital twin models

JH Oh, S Sfarra, EJ Kim - Energy and Buildings, 2024 - Elsevier
To achieve net zero emissions in the building and construction sector, there is a growing
interest in how buildings can be digitalized to improve energy efficiency through optimal …

Automatic pavement crack identification based on an improved C-mask region-based convolutional neural network model

L ** an intelligent transportation
system. The traditional approach of in-situ inspection is expensive and requires more man …

[HTML][HTML] 병렬 병합 구조를 이용한 기상 데이터의 예측률 향상을 위한 딥러닝 모델

김창복 - 한국정보기술학회논문지, 2022 - ki-it.com
초록 본 연구는 딥러닝 기본모델인 DNN, LSTM, BiLSTM, 1D-CNN 등으로, 예측의 성능을
향상하기 위해, 중간층을 병렬로 병합하는 구조를 제안하였다. 제안모델 1 은 동일한 …