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https://doi.org/10.2139/ssrn.4656380
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-58452-8_43openalex-extracted
Prototype Rectification for Few-Shot Learning
inferredcites →https://doi.org/10.1007/978-3-030-58548-8_26openalex-extracted
Negative Margin Matters: Understanding Margin in Few-Shot Classification
inferredcites →https://doi.org/10.1007/978-3-030-58568-6_16openalex-extracted
Rethinking Few-Shot Image Classification: A Good Embedding is All You Need?
inferredcites →https://doi.org/10.1016/j.compeleceng.2013.11.024openalex-extracted
A survey on feature selection methods
inferredcites →https://doi.org/10.1016/j.patcog.2021.107935openalex-extracted
Local descriptor-based multi-prototype network for few-shot Learning
inferredcites →https://doi.org/10.1016/j.patcog.2022.108792openalex-extracted
Learning attention-guided pyramidal features for few-shot fine-grained recognition
inferredcites →https://doi.org/10.1016/j.patcog.2022.108986openalex-extracted
Few-shot learning with unsupervised part discovery and part-aligned similarity
inferredcites →https://doi.org/10.1016/j.patcog.2022.109024openalex-extracted
SaberNet: Self-attention based effective relation network for few-shot learning
inferredcites →https://doi.org/10.1016/j.patcog.2022.109170openalex-extracted
SAPENet: Self-Attention based Prototype Enhancement Network for Few-shot Learning
inferredcites →https://doi.org/10.1016/j.patcog.2023.109468openalex-extracted
Cycle optimization metric learning for few-shot classification
inferredcites →https://doi.org/10.1016/j.patcog.2023.109811openalex-extracted
Cross-Domain Few-Shot classification via class-shared and class-specific dictionaries
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-extracted
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2017.354openalex-extracted
Network Dissection: Quantifying Interpretability of Deep Visual Representations
inferredcites →https://doi.org/10.1109/cvpr.2018.00131openalex-extracted
Learning to Compare: Relation Network for Few-Shot Learning
inferredcites →https://doi.org/10.1109/cvpr.2019.00672openalex-extracted
Few-Shot Learning With Localization in Realistic Settings
inferredcites →https://doi.org/10.1109/cvpr.2019.00743openalex-extracted
Revisiting Local Descriptor Based Image-To-Class Measure for Few-Shot Learning
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00883openalex-extracted
Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01222openalex-extracted
DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover’s Distance and Structured Classifiers
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00514openalex-extracted
Learning Dynamic Alignment via Meta-filter for Few-shot Learning
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00792openalex-extracted
Few-Shot Classification with Feature Map Reconstruction Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01069openalex-extracted
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00526openalex-extracted
Task Discrepancy Maximization for Fine-grained Few-Shot Classification
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00781openalex-extracted
Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00881openalex-extracted
Matching Feature Sets for Few-Shot Image Classification
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01401openalex-extracted
Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01921openalex-extracted
Revisiting Prototypical Network for Cross Domain Few-Shot Learning
inferredcites →https://doi.org/10.1109/iccv48922.2021.00890openalex-extracted
On the Importance of Distractors for Few-Shot Classification
inferredcites →https://doi.org/10.1109/iccv48922.2021.00929openalex-extracted
Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder
inferredcites →https://doi.org/10.1109/iccv48922.2021.00933openalex-extracted
Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning
inferredcites →https://doi.org/10.1109/iccvw.2013.77openalex-extracted
3D Object Representations for Fine-Grained Categorization
inferredcites →https://doi.org/10.1109/tcsvt.2022.3232717openalex-extracted
Improving the Generalization of MAML in Few-Shot Classification via Bi-Level Constraint
inferredcites →https://doi.org/10.1109/tip.2022.3143692openalex-extracted
Imposing Semantic Consistency of Local Descriptors for Few-Shot Learning
inferredcites →https://doi.org/10.1109/wacv.2018.00097openalex-extracted
Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks
inferredcites →https://doi.org/10.1609/aaai.v36i2.20076openalex-extracted
DMN4: Few-Shot Learning via Discriminative Mutual Nearest Neighbor Neural Network
inferredcites →https://doi.org/10.1609/aaai.v37i1.25150openalex-extracted
RankDNN: Learning to Rank for Few-Shot Learning
inferredcites →https://doi.org/10.1609/aaai.v37i7.26016openalex-extracted
SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning
inferredcites →https://doi.org/10.2478/cait-2019-0001openalex-extracted
A Review of Feature Selection and Its Methods
inferredcites →https://doi.org/10.24963/ijcai.2020/409openalex-extracted
Asymmetric Distribution Measure for Few-shot Learning
inferredcites →https://doi.org/10.24963/ijcai.2021/149openalex-extracted
Cross-Domain Few-Shot Classification via Adversarial Task Augmentation
inferredcites →https://doi.org/10.48550/arxiv.1412.6856openalex-extracted
Object Detectors Emerge in Deep Scene CNNs
inferredcites →https://doi.org/10.48550/arxiv.1703.05175openalex-extracted
Prototypical Networks for Few-shot Learning
inferredcites →https://doi.org/10.48550/arxiv.1709.01507openalex-extracted
Squeeze-and-Excitation Networks
inferredcites →https://doi.org/10.48550/arxiv.1803.00676openalex-extracted
Meta-Learning for Semi-Supervised Few-Shot Classification
inferredcites →https://doi.org/10.48550/arxiv.1904.04232openalex-extracted
A Closer Look at Few-shot Classification
inferredcites →https://doi.org/10.48550/arxiv.2001.08735openalex-extracted
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation
inferredcites →https://doi.org/10.48550/arxiv.2008.08882openalex-extracted
BOIL: Towards Representation Change for Few-shot Learning
inferredcites →https://doi.org/10.48550/arxiv.2206.08126openalex-extracted
Channel Importance Matters in Few-Shot Image Classification
inferredcites →https://doi.org/10.57702/i9oeewf6openalex-extracted
Caltech-UCSD Birds-200-2011 Dataset
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