Deep Learning-Based Automated Image Segmentation for Concrete Petrographic Analysis

[1]  Daniel I. Castaneda,et al.  A 3D petrographic analysis for concrete freeze-thaw protection , 2020 .

[2]  Jinjun Xiong,et al.  SPGNet: Semantic Prediction Guidance for Scene Parsing , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[3]  Yunchao Wei,et al.  Devil in the Details: Towards Accurate Single and Multiple Human Parsing , 2018, AAAI.

[4]  D. Lange,et al.  A Performance-Based Approach to Concrete Freeze-Thaw Durability , 2018 .

[5]  Kyle A. Riding,et al.  Advances in measuring air-void parameters in hardened concrete using a flatbed scanner , 2017 .

[6]  George Papandreou,et al.  Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.

[7]  Matthew B. Blaschko,et al.  The Lovasz-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[8]  José García Rodríguez,et al.  A Review on Deep Learning Techniques Applied to Semantic Segmentation , 2017, ArXiv.

[9]  G. Litjens,et al.  A survey on deep learning in medical image analysis , 2017, Medical Image Anal..

[10]  J. Wawrzeńczyk,et al.  Protected Paste Volume (PPV) as a parameter linking the air-pore structure in concrete with the frost resistance results , 2016 .

[11]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Yi Yang,et al.  Attention to Scale: Scale-Aware Semantic Image Segmentation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Jianxiong Xiao,et al.  DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[14]  Iasonas Kokkinos,et al.  Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.

[15]  Pedro H. O. Pinheiro,et al.  From image-level to pixel-level labeling with Convolutional Networks , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Trevor Darrell,et al.  Fully convolutional networks for semantic segmentation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[18]  Jitendra Malik,et al.  Simultaneous Detection and Segmentation , 2014, ECCV.

[19]  Ali Akbar Ramezanianpour,et al.  Effect of New Composite Cement Containing Volcanic Ash and Limestone on Mechanical Properties and Salt Scaling Resistance of Concrete , 2013 .

[20]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[21]  A. Hussin,et al.  Petrography evidence of the interfacial transition zone (ITZ) in the normal strength concrete containing granitic and limestone aggregates , 2011 .

[22]  Jeremy P. Ingham,et al.  Application of petrographic examination techniques to the assessment of fire-damaged concrete and masonry structures , 2009 .

[23]  R. Přikryl,et al.  Petrographic identification of alkali–silica reactive aggregates in concrete from 20th century bridges , 2009 .

[24]  Frank Fueten,et al.  An artificial neural net assisted approach to editing edges in petrographic images collected with the rotating polarizer stage , 2007, Comput. Geosci..

[25]  Min-hong Zhang,et al.  Hydration of cement and pore structure of concrete cured in tropical environment , 2006 .

[26]  Lawrence L. Sutter,et al.  Petrographic evidence of calcium oxychloride formation in mortars exposed to magnesium chloride solution , 2006 .

[27]  G. De Schutter,et al.  Automated air void analysis of hardened concrete — a Round Robin study , 2006 .

[28]  Jan Elsen,et al.  Microscopy of historic mortars—a review , 2006 .

[29]  Katrin Rübner,et al.  The microstructure of concrete made with municipal waste incinerator bottom ash as an aggregate component , 2006 .

[30]  K. Peterson,et al.  Crystallized alkali-silica gel in concrete from the late 1890s , 2006 .

[31]  B. Georgali,et al.  Microstructure of fire-damaged concrete. A case study , 2005 .

[32]  T. Katayama How to identify carbonate rock reactions in concrete , 2004 .

[33]  S. Marfil,et al.  Deteriorated pavements due to the alkali–silica reaction: A petrographic study of three cases in Argentina , 2001 .

[34]  Michel Pigeon,et al.  Some findings on the usefulness of image analysis for determining the characteristics of the air-void system on hardened concrete , 2001 .

[35]  N. R. Short,et al.  Determination of bond strength in glass fibre reinforced cement using petrography and image analysis , 2000 .

[36]  Ray G. Gosine,et al.  Automated image analysis for applications in reservoir characterization , 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

[37]  David A Lange,et al.  Quantitative Image Analysis of Masonry Mortar Microstructure , 1999 .

[38]  Stan Matwin,et al.  Machine Learning for the Detection of Oil Spills in Satellite Radar Images , 1998, Machine Learning.

[39]  Wei-Ming Lin,et al.  Microstructures of Fire-Damaged Concrete , 1996 .

[40]  Yunchao Wei,et al.  A PyTorch Semantic Segmentation Toolbox , 2018 .

[41]  O. Çopuroğlu,et al.  Quantitative Energy-Dispersive X-Ray Microanalysis of Chlorine in Cement Paste , 2016 .

[42]  S. Mallat,et al.  A Wavelet Tour of Signal Processing : The Sparse Way , 2008 .

[43]  Farhad Ansari,et al.  AUTOMATED DETERMINATION OF ENTRAINED AIR-VOID PARAMETERS IN HARDENED CONCRETE , 2005 .

[44]  Thomas J. Van Dam,et al.  Hardened Concrete Air Void Analysis with a Flatbed Scanner , 2001 .

[45]  S. Mallat II – Fourier kingdom , 1999 .

[46]  S. Mallat A wavelet tour of signal processing , 1998 .

[47]  J Cahill,et al.  The Identification and Measurement of Entrained Air in Concrete using Image Analysis , 1994 .

[48]  P. Stutzman Applications of Scanning Electron Microscopy in Cement and Concrete Petrography , 1994 .