HIGHLIGHTS
- who: TYPE and collaborators from the University of Electronic Science and Technology of China, China have published the paper: March 2023 10.3389/feart.2023.1073211, in the Journal: (JOURNAL) of 10/03/2023
- what: The authors show that the U-Net convolutional neural_network, semantic segmentation and transfer learning can be used to accurately detect cracks in drone photos of sedimentary massifs. The U-Net design was chosen for the following reasons. i where the authors use the constant u03b3=2.
- how: For relabeling the authors used another 4 000 u00d7 2000 photo . . .
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