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Found 4 papers, 0 papers with code
BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation
We introduce BTSeg, an innovative, semi-supervised training approach enhancing semantic segmentation models in order to effectively handle a range of adverse conditions without requiring the creation of extensive new datasets.
System for 3D Acquisition and 3D Reconstruction using Structured Light for Sewer Line Inspection
The assessment of sewer pipe systems is a highly important, but at the same time cumbersome and error-prone task.
From Explanations to Segmentation: Using Explainable AI for Image Segmentation
The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision.
Explainable Artificial Intelligence (XAI)
Image Segmentation
+3
Automatic Analysis of Sewer Pipes Based on Unrolled Monocular Fisheye Images
The task of detecting and classifying damages in sewer pipes offers an important application area for computer vision algorithms.
