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A Survey on Visual Transfer Learning using Knowledge Graphs
[article]
2022
arXiv
pre-print
Recent approaches of computer vision utilize deep learning methods as they perform quite well if training and testing domains follow the same underlying data distribution. However, it has been shown that minor variations in the images that occur when using these methods in the real world can lead to unpredictable errors. Transfer learning is the area of machine learning that tries to prevent these errors. Especially, approaches that augment image data using auxiliary knowledge encoded in
arXiv:2201.11794v1
fatcat:tapql5h4j5dvrnxjkaxek2cquu