Neural inference search for multiloss segmentation models
Semantic segmentation is vital for many emerging surveillance applications, but current
models cannot be relied upon to meet the required tolerance, particularly in complex tasks …
models cannot be relied upon to meet the required tolerance, particularly in complex tasks …
A single latent channel is sufficient for biomedical glottis segmentation
AM Kist, K Breininger, M Dörrich, S Dürr… - Scientific Reports, 2022 - nature.com
Glottis segmentation is a crucial step to quantify endoscopic footage in laryngeal high-speed
videoendoscopy. Recent advances in deep neural networks for glottis segmentation allow …
videoendoscopy. Recent advances in deep neural networks for glottis segmentation allow …
Using layer-wise training for road semantic segmentation in autonomous cars
A recently developed application of computer vision is pathfinding in self-driving cars.
Semantic scene understanding and semantic segmentation, as subfields of computer vision …
Semantic scene understanding and semantic segmentation, as subfields of computer vision …
Global and Local Features Through Gaussian Mixture Models on Image Semantic Segmentation
The semantic segmentation task aims at dense classification at the pixel-wise level. Deep
models exhibited progress in tackling this task. However, one remaining problem with these …
models exhibited progress in tackling this task. However, one remaining problem with these …
A single latent channel is sufficient for biomedical image segmentation
Glottis segmentation is a crucial step to quantify endoscopic footage in laryngeal high-speed
videoendoscopy. Recent advances in using deep neural networks for glottis segmentation …
videoendoscopy. Recent advances in using deep neural networks for glottis segmentation …