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Found 9 papers, 1 papers with code
MDFM: Multi-Decision Fusing Model for Few-Shot Learning
Inspired by this assumption, we propose a novel method Multi-Decision Fusing Model (MDFM), which comprehensively considers the decisions based on multiple FEMs to enhance the efficacy and robustness of the model.
MHFC: Multi-Head Feature Collaboration for Few-Shot Learning
Apply the trained FEM to acquire the novel data's features and recognize them.
CIM: Class-Irrelevant Mapping for Few-Shot Classification
(2) Use the FEM to extract the features of novel data (with few labeled samples and totally different categories from base data), then classify them with the to-be-designed classifier.
DLDL: Dynamic Label Dictionary Learning via Hypergraph Regularization
To tackle this issue, we propose a Dynamic Label Dictionary Learning (DLDL) algorithm to generate the soft label matrix for unlabeled data.
SAHDL: Sparse Attention Hypergraph Regularized Dictionary Learning
In this paper, we propose a hypergraph based sparse attention mechanism to tackle this issue and embed it into dictionary learning.
Class specific or shared? A cascaded dictionary learning framework for image classification
Dictionary learning methods can be split into: i) class specific dictionary learning ii) class shared dictionary learning.
Label Embedded Dictionary Learning for Image Classification
Recently, label consistent k-svd (LC-KSVD) algorithm has been successfully applied in image classification.
Multi-view Face Analysis Based on Gabor Features
Different methods of classification based on sparse representation and Gabor kernels have been widely applied in the fields of facial analysis.
Dictionary learning based image enhancement for rarity detection
Image enhancement is an important image processing technique that processes images suitably for a specific application e. g. image editing.
