Effective medium crack classification on laboratory concrete specimens via competitive machine learning

Explainable machine learning using real, synthetic and augmented fire tests to predict fire resistance and spalling of RC columns

(2022) M.Z. Naser et al.   ENGINEERING STRUCTURES

Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning

(2021) Dimitris Dais et al.   AUTOMATION IN CONSTRUCTION

Concrete compressive strain behavior and magnitudes under uniaxial fatigue loading

(2021) Somashekar Viswanath et al.   CONSTRUCTION AND BUILDING MATERIALS

Testing and numerical modelling of circular CFDST cross-sections with stainless steel outer tubes in bending

(2021) Fangying Wang et al.   ENGINEERING STRUCTURES

Machine Learning Classifiers for Surface Crack Detection in Fracture Experiments

(2021) Adrien Müller et al.   INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES

Combining computer vision with semantic reasoning for on-site safety management in construction

(2021) Haitao Wu et al.   Journal of Building Engineering

A multi-layer approach to classify the risk of corrosion in concrete specimens that contain different additives

(2021) José A. Guzmán-Torres et al.   Case Studies in Construction Materials

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection

(2020) Qiaoning Yang et al.   AUTOMATION IN CONSTRUCTION

Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning

(2020) Dongho Kang et al.   AUTOMATION IN CONSTRUCTION

A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour

(2020) Xinyi Li et al.   ENERGY

Durability and shrinkage performance of concrete made with coarse multi-recycled concrete aggregates

(2020) Stefano Silva et al.   CONSTRUCTION AND BUILDING MATERIALS

Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network

(2019) Shengyuan Li et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Encoder-decoder network for pixel-level road crack detection in black-box images

(2019) Seongdeok Bang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Segmentation-based deep-learning approach for surface-defect detection

(2019) Domen Tabernik et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Concrete Cracks Detection Based on FCN with Dilated Convolution

(2019) Jianming Zhang et al.   Applied Sciences-Basel

Computer vision-based concrete crack detection using U-net fully convolutional networks

(2019) Zhenqing Liu et al.   AUTOMATION IN CONSTRUCTION

Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

(2019) Chuncheng Feng et al.   KSCE Journal of Civil Engineering

Artificial intelligence in seismology: Advent, performance and future trends

(2019) Pengcheng Jiao et al.   Geoscience Frontiers

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

(2018) Zaher Mundher Yaseen et al.   ADVANCES IN ENGINEERING SOFTWARE

Compressive strength prediction of recycled concrete based on deep learning

(2018) Fangming Deng et al.   CONSTRUCTION AND BUILDING MATERIALS

A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete

(2018) Dac-Khuong Bui et al.   CONSTRUCTION AND BUILDING MATERIALS

SEISMIC FACIES ANALYSIS USING MACHINE-LEARNING

(2018) T. Wrona et al.   GEOPHYSICS

Deep Learning–Based Fully Automated Pavement Crack Detection on 3D Asphalt Surfaces with an Improved CrackNet

(2018) Allen Zhang et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Autonomous concrete crack detection using deep fully convolutional neural network

(2018) Cao Vu Dung et al.   AUTOMATION IN CONSTRUCTION