The analysis of Magnetic Resonance Imaging (MRI) sequences enables clinical professionals to monitor the progression of a brain tumor.
Modern lane detection methods have achieved remarkable performances in complex real-world scenarios, but many have issues maintaining real-time efficiency, which is important for autonomous vehicles.
Ranked #6 on Lane Detection on LLAMAS
The method does not aim at overcoming the training with real data, but to be a compatible alternative when the real data is not available.
One of the main factors that contributed to the large advances in autonomous driving is the advent of deep learning.
Ranked #9 on Lane Detection on LLAMAS
To implement this idea we derive specialized deep models for each domain by adapting a pre-trained architecture but, differently from other methods, we propose a novel strategy to automatically adjust the computational complexity of the network.