Feb 13, 2024 · This paper proposes a semi-dynamic ensemble pruning algorithm (SDEP) to implement the FER task. First, a subspace-based classifier sequences selection method ...
An efficient semi-dynamic ensemble pruning method for facial expression recognition ; Journal: Multimedia Tools and Applications, 2024, № 30, p. 73923-73956.
TL;DR: A method for combining classifiers that use estimates of each individual classifier's local accuracy in small regions of feature space surrounding an ...
Like all other dynamic ensemble pruning methods, GDEP can be divided into three steps: 1) Construct the neighborhood; 2) Evaluate the classifiers' performance; ...
Dynamic ensemble pruning (DEP) can select the best set of models for an unseen sample to improve a classification system's prediction accuracy and robustness.
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Sep 17, 2022 · We propose a Component based Ensemble Stacked Convolution Neural Networks CES-CNN to recognize facial expressions from partially occluded faces.
Missing: efficient | Show results with:efficient
Sep 8, 2021 · SMMFA efficiently reduces the dimension of the facial features and thus helps in extracting discriminant features for FER. In another work, Li ...
Automatic facial expression recognition (FER) is an important technique ... An efficient semi-dynamic ensemble pruning method for facial expression recognition.
An efficient semi-dynamic ensemble pruning method for facial expression recognition · Explainable online ensemble of deep neural network pruning for time series ...
Mar 19, 2024 · We employ a semi-supervised learning technique to generate expression category pseudo-labels for unlabeled face data.