An active learning framework featured Monte Carlo dropout strategy for deep learning-based semantic segmentation of concrete cracks from images
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
An active learning framework featured Monte Carlo dropout strategy for deep learning-based semantic segmentation of concrete cracks from images
Authors
Keywords
-
Journal
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
Volume -, Issue -, Pages 147592172211503
Publisher
SAGE Publications
Online
2023-02-06
DOI
10.1177/14759217221150376
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Automated Pavement Crack Damage Detection Using Deep Multiscale Convolutional Features
- (2020) Weidong Song et al. JOURNAL OF ADVANCED TRANSPORTATION
- Ensemble of Deep Convolutional Neural Networks for Automatic Pavement Crack Detection and Measurement
- (2020) Zhun Fan et al. Coatings
- Automatic Pixel-Level Crack Detection on Dam Surface Using Deep Convolutional Network
- (2020) Chuncheng Feng et al. SENSORS
- CrackU-net: A novel deep convolutional neural network for pixelwise pavement crack detection
- (2020) Ju Huyan et al. Structural Control & Health Monitoring
- Anomaly detection of defects on concrete structures with the convolutional autoencoder
- (2020) J.K. Chow et al. ADVANCED ENGINEERING INFORMATICS
- A vision-based active learning convolutional neural network model for concrete surface crack detection
- (2020) Zhen Wang et al. ADVANCES IN STRUCTURAL ENGINEERING
- Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning
- (2020) Dongho Kang et al. AUTOMATION IN CONSTRUCTION
- Artificial intelligence-empowered pipeline for image-based inspection of concrete structures
- (2020) Jun Kang Chow et al. AUTOMATION IN CONSTRUCTION
- Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring
- (2019) Billie F. Spencer et al. Engineering
- Autonomous bolt loosening detection using deep learning
- (2019) Yang Zhang et al. STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
- DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
- (2019) Yahui Liu et al. NEUROCOMPUTING
- Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder–Decoder Network
- (2019) M. M. Manjurul Islam et al. SENSORS
- Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks
- (2019) Mohamad Alipour et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Image-based concrete crack detection in tunnels using deep fully convolutional networks
- (2019) Yupeng Ren et al. CONSTRUCTION AND BUILDING MATERIALS
- Cost-Effective Vehicle Type Recognition in Surveillance Images With Deep Active Learning and Web Data
- (2019) Yue Huang et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- SDDNet: Real-Time Crack Segmentation
- (2019) Wooram Choi et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion
- (2018) Fu-Chen Chen et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Pixel-level crack delineation in images with convolutional feature fusion
- (2018) FuTao Ni et al. Structural Control & Health Monitoring
- DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
- (2018) Qin Zou et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Autonomous concrete crack detection using deep fully convolutional neural network
- (2018) Cao Vu Dung et al. AUTOMATION IN CONSTRUCTION
- Cost-Effective Active Learning for Deep Image Classification
- (2017) Keze Wang et al. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
- Leveraging uncertainty information from deep neural networks for disease detection
- (2017) Christian Leibig et al. Scientific Reports
- A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure
- (2015) Christian Koch et al. ADVANCED ENGINEERING INFORMATICS
- Active deep learning method for semi-supervised sentiment classification
- (2013) Shusen Zhou et al. NEUROCOMPUTING
- Semantic object classes in video: A high-definition ground truth database
- (2008) Gabriel J. Brostow et al. PATTERN RECOGNITION LETTERS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now