Unsupervised PolSAR image classification based on sparse representation
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2019.1587209
Abstract: ABSTRACT A novel unsupervised image classification algorithm which based on the sparse representation theory for polarimetric synthetic aperture radar (PolSAR) image is introduced in this paper. The algorithm conjunctively uses sparse representation-based classification (SRC) theory,… read more here.
Keywords: based sparse; sparse representation; classification; class labels ... See more keywords
Explainable Reverse Verification of Goodness of Classification of MRI Images by Clinical Experts.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2023.3280184
Abstract: Radiology offers a presumptive diagnosis. The etiology of radiological errors are prevalent, recurrent, and multi-factorial. The pseudo-diagnostic conclusions can arise from varying factors such as, poor technique, failures of visual perception, lack of knowledge, and… read more here.
Keywords: reverse verification; class labels; classification; class ... See more keywords
Task-Specific Loss for Robust Instance Segmentation with Noisy Class Labels
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3109084
Abstract: Deep learning methods have achieved significant progress in the presence of correctly annotated datasets in instance segmentation. However, object classes in large-scale datasets are sometimes ambiguous, which easily causes confusion. Besides, limited experience and knowledge… read more here.
Keywords: class; noisy class; instance segmentation; class labels ... See more keywords
Skeleton-Based Human Motion Prediction With Privileged Supervision.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3166861
Abstract: Existing supervised methods have achieved impressive performance in forecasting skeleton-based human motion. However, they often rely on action class labels in both training and inference phases. In practice, it could be a burden to request… read more here.
Keywords: action class; based human; human motion; skeleton based ... See more keywords