3 papers
cs.CV2019
Towards Robust Learning with Different Label Noise Distributions
Diego Ortego, Eric Arazo, Paul Albert +2
Noisy labels are an unavoidable consequence of labeling processes and detecting them is an important step towards preventing performance degradations in Convolutional Neural Networ…
cs.CV2019
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Eric Arazo, Diego Ortego, Paul Albert +2
Semi-supervised learning, i.e. jointly learning from labeled and unlabeled samples, is an active research topic due to its key role on relaxing human supervision. In the context of…
cs.CV2019
On guiding video object segmentation
Diego Ortego, Kevin McGuinness, Juan C. SanMiguel +3
This paper presents a novel approach for segmenting moving objects in unconstrained environments using guided convolutional neural networks. This guiding process relies on foregrou…