A multi-scale regional convolution neural network method for detecting outcrop cavities is proposed. •. The method has higher accuracy than the traditional ...
Mar 1, 2022 · A multi-scale regional convolution neural network method for detecting outcrop cavities is proposed. •. The method has higher accuracy than the ...
By enhancing the deep-learning model of a convolution neural network, the mask region-convolutional neural network (Mask R-CNN) is proposed. This method adapts ...
Mask R-CNN for Automatic-Extraction-of-Outcrop-Cavity. This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates ...
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Automatic extraction of outcrop cavity based on a multiscale regional convolution neural network ... Automatic extraction based on convolutional neural networks ...
Wu, Automatic extraction of outcrop cavity based on a multiscale regional convolution neural network, Comput. Geosci., № 160 https://doi.org/10.1016/j.cageo ...
Automatic Extraction of Outcrop Cavity Based on Multi-scale Regional Convolution Neural Network. Geoscience 2021, 35, 1147. [Google Scholar]; Bemis, S ...
In this method, criteria based on the local surface normal and curvature of the point cloud are used to initiate and control the growth of the fracture region.
[13] proposed an object-based deep CNN framework for extracting information about different types of buildings. They tested their approach on aerial imagery of ...
Missing: outcrop cavity
