7 citations · 7 across the 2 of their papers we have counts for
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cs.CV2018
Dynamic Adaptation on Non-Stationary Visual Domains
Sindi Shkodrani, Michael Hofmann, Efstratios Gavves
Domain adaptation aims to learn models on a supervised source domain that perform well on an unsupervised target. Prior work has examined domain adaptation in the context of statio…
cs.CV2018
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
Mohsen Ghafoorian, Cedric Nugteren, Nóra Baka +2
Convolutional neural networks have been successfully applied to semantic segmentation problems. However, there are many problems that are inherently not pixel-wise classification p…