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Found 5 papers, 5 papers with code
CBA: Improving Online Continual Learning via Continual Bias Adaptor
Online continual learning (CL) aims to learn new knowledge and consolidate previously learned knowledge from non-stationary data streams.
Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
The core idea is to automatically assimilate the training bias caused by class imbalance via the bias adaptive classifier, which is composed of a novel bias attractor and the original linear classifier.
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers
Existing methods commonly address hierarchical classification by decoupling it into a series of multi-class classification tasks.
FOCNet: A Fractional Optimal Control Network for Image Denoising
Recent studies on the mathematical foundation of DCNN has revealed that the forward propagation of DCNN corresponds to a dynamic system, which can be described by an ordinary differential equation (ODE) and solved by the optimal control method.
A Benchmark for Edge-Preserving Image Smoothing
This benchmark includes an image dataset with groundtruth image smoothing results as well as baseline algorithms that can generate competitive edge-preserving smoothing results for a wide range of image contents.
