The dataset includes 458 hi-res images together with their alpha maps (BW) indicating the crack presence. The ground truth for semantic segmentation has two classes to conduct binary pixelwise classification. The photos are captured in various buildings located in Middle East Technical University. You can access a larger dataset containing images with 227x227 px dimensions for classification which are produced from this dataset from http://dx.doi.org/10.17632/5y9wdsg2zt.1
Cracks on the concrete surface are one of the earliest indications of degradation of the structure w...
This study proposes a machine learning-based concrete crack identification strategy using digital im...
Cracks on concrete infrastructure are one of the early indications of structural degradation which n...
The dataset includes 458 hi-res images together with their alpha maps (BW) indicating the crack pres...
This is a concrete crack dataset for segmentation. It is partially from Ozgenel FÇ. Concrete crack s...
The dataset contains concrete images having cracks. The data is collected from various METU Campus B...
Abstract Monitoring of structures’ condition plays a fundamental role in providing safety for users ...
SDNET2018 is an annotated image dataset for training, validation, and benchmarking of artificial int...
This paper presents an algorithm detecting automatically a wide variety of cracks on monochrome imag...
Abstract- Cracks in concrete buildings may show the total extent of damage or problems of greater ma...
The NCCD-PF dataset was developed for the classification and semantic segmentation of narrow concret...
In this paper, we exploit the concrete surface flaw inspection through the fusion of visual position...
Traditional crack assessment methods for concrete structures are time consuming and produce subjecti...
In concrete structures, surface cracks are important indicators of structural durability and service...
Dataset for training CNN built from aerial drone images of buildings in Hamburg This dataset contai...
Cracks on the concrete surface are one of the earliest indications of degradation of the structure w...
This study proposes a machine learning-based concrete crack identification strategy using digital im...
Cracks on concrete infrastructure are one of the early indications of structural degradation which n...
The dataset includes 458 hi-res images together with their alpha maps (BW) indicating the crack pres...
This is a concrete crack dataset for segmentation. It is partially from Ozgenel FÇ. Concrete crack s...
The dataset contains concrete images having cracks. The data is collected from various METU Campus B...
Abstract Monitoring of structures’ condition plays a fundamental role in providing safety for users ...
SDNET2018 is an annotated image dataset for training, validation, and benchmarking of artificial int...
This paper presents an algorithm detecting automatically a wide variety of cracks on monochrome imag...
Abstract- Cracks in concrete buildings may show the total extent of damage or problems of greater ma...
The NCCD-PF dataset was developed for the classification and semantic segmentation of narrow concret...
In this paper, we exploit the concrete surface flaw inspection through the fusion of visual position...
Traditional crack assessment methods for concrete structures are time consuming and produce subjecti...
In concrete structures, surface cracks are important indicators of structural durability and service...
Dataset for training CNN built from aerial drone images of buildings in Hamburg This dataset contai...
Cracks on the concrete surface are one of the earliest indications of degradation of the structure w...
This study proposes a machine learning-based concrete crack identification strategy using digital im...
Cracks on concrete infrastructure are one of the early indications of structural degradation which n...