Covision Lab’s Post

🧠 Last week at Covision Lab, we held an internal tech session on Unsupervised Domain Adaptation (UDA) and Domain Generalization - two complementary approaches for improving the robustness of vision models under domain shift between training and deployment. 🌍🤖 We explored how these methods enable models to transfer knowledge across visual domains without relying on labeled target data. The session covered key techniques such as DANN, FCN in the Wild, Maximum Classifier Discrepancy (MCD), CORAL, DLOW, and MixStyle, highlighting how they align feature distributions or manipulate style statistics to mitigate the effects of domain shift. It was an engaging discussion that sparked new ideas on applying domain adaptation and generalization techniques across multiple projects at Covision Lab. 🚀   #TechSession #DomainAdaptation #DomainGeneralization #ComputerVision #DeepLearning #AIResearch

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