Few-Shot Learning
|
|
|
FCGNN: Fuzzy Cognitive Graph Neural Networks with Concept Evolution for Few-Shot Learning |
|
|
|
FSAKE: Few-shot graph learning via adaptive neighbor class knowledge embedding |
|
|
|
FSPDF: Few-shot learning with progressive dual-domain feature fusion via self-supervised learning |
|
|
|
Few-shot Learning with Multi-Granularity Knowledge Fusion and Decision-Making |
|
|
|
CSTS: Exploring class-specific and task-shared embedding representation for few-shot learning |
|
|
|
HMRM: Hierarchy-awareness misclassification risk minimization for few-shot learning |
|
|
|
Hierarchical few-shot learning with feature fusion driven by data and knowledge |
|
|
|
Hierarchical few-shot learning based on coarse- and fine-grained relation network |
|
|
|
Self-similarity Feature Based Few-shot Learning via Hierarchical Relation Network |
 | |
| Few-shot learning based on hierarchical classification via multi-granularity relation networks |
Feature Selection
|
|
|
PHFS: Progressive Hierarchical Feature Selection Based on Adaptive Sample Weighting |
|
|
|
DMTFS-FO: Dynamic multi-task feature selection based on flexible loss and orthogonal constraint |
|
|
|
Feature selection via maximizing inter-class independence and minimizing intra-class redundancy for hierarchical classification |
|
|
|
FS-MGKC: Feature selection based on structural manifold learning with multi-granularity knowledge coordination |
|
|
|
Robust hierarchical feature selection driven by data and knowledge |
|
|
|
Hierarchical feature selection with multi-granularity clustering structure |
Long-Tailed classification
|
|
|
DPA-EI: Long-tailed classification by dual progressive augmentation from explicit and implicit perspectives |
|
|
|
ECS-SC: Long-tailed classification via data augmentation based on easily confused sample selection and combination |
|
|
|
Hierarchical long-tailed classification based on coarse- to fine-grained knowledge transfer driven by feature fusion |
|
|
|
Hierarchical convolutional neural network with knowledge complementation for long-tailed classification |
|
|
|
Coarse-to-fine knowledge transfer based long-tailed classification via bilateral-sampling network |
|
|
|
Multi-task convolutional neural network with coarse-to-fine knowledge transfer for long-tailed classification |
|
|
|
Hybrid ResNet based on joint basic and attention modules for long-tailed classification |