Deep metric learning for few-shot image classification: A Review of recent developments

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DuaL-branch similarity network with Bi-correlative attention for few-shot Shui script recognition

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Class-Discrepancy Dynamic Weighting for Cross-Domain Few-Shot Hyperspectral Image Classification

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Federated Learning Architecture for 3D Breast Cancer Image Classification

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Few-shot learning and explainable AI for colon cancer histopathology: A prototypical network with multi-technique interpretability

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Relationship constraint deep metric learning

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Image retrieval using deep saliency edge feature

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New technology for pipeline defect detection

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DBA-RMCL: Refined Metric Contrastive Learning With Dual-Branch Attention for Few-Shot Remote Sensing Image Scene Classification

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Interactive triplet attention for few-shot fine-grained image classification

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Integrating novel convolutional neural network with prototype learning for rotating machinery fault diagnosis under small sample

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Semi-supervised few-shot learning via ensemble-based adaptive clustering-aware pseudo-labeling

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Sig-RFPNet: multi-branch network and multi-classifier method for offline signature recognition

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KiRV: Robust Human Identification via Multimodal Learning Based on Kinetic Gait Features of Radar and Vision

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Few-Shot Learning for Multiclass Disease Detection in Azadirachta Indica

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Hyperspectral Image Few-Shot Classification Based on Spatial–Spectral Information Complementation and Multilatent Domain Generalization

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A novel framework GRCornShot for corn disease detection using few shot learning with prototypical network

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A review on the effectiveness of recent approaches to few-shot learning for image analysis

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ScribbleCDNet: Change detection on high-resolution remote sensing imagery with scribble interaction

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Weighted unsupervised domain adaptation considering geometry features and engineering performance of 3D design data

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Fully cooperative domain adaptive neural network for defect classification in printed circuit boards

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BMPCN: A Bigraph Mutual Prototype Calibration Net for few-shot classification

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TALDS: A Transfer-Active Learning-Driven Siamese Network for Bi-temporal Image Classification

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LmGa: Combining label mapping method with graph attention network for agricultural recognition

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Difficulties in Using Synthetic Data for Presentation Attack Detection in Finger Vein Recognition: The Role of Model Fingerprints

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Developing artificial mechanics intuitions from extremely small data

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Discriminative distance metric learning via class-center guidance

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Few-shot radar emitter signal recognition based on prototype network with filter system

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Knowledge-guided distribution alignment for cross-domain few-shot learning

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A lightweight and real-time deep learning approach for pipeline bolt loosening detection using active guided waves

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CellPredX, a computational framework for cross-data type, cross-sample, and cross-protocol cell type annotation through domain adaptation and deep metric learning

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Local Contrast Learning for One-Shot Learning

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A convex Kullback–Leibler optimization for semi-supervised few-shot learning

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Multi-view prototype balance and temporary proxy constraint for exemplar-free class-incremental learning

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Multi-modal Few-shot Image Recognition with enhanced semantic and visual integration

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Few-shot tire tracks recognition based on metric learning

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A review of few-shot image recognition using semantic information

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Advanced Global Prototypical Segmentation Framework for Few-Shot Hyperspectral Image Classification

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ZooKT: Task-adaptive knowledge transfer of Model Zoo for few-shot learning

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Bias to Balance: New-Knowledge-Preferred Few-Shot Class-Incremental Learning via Transition Calibration

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Cross-modal de-deviation for enhancing few-shot classification

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Few-shot SAR image classification： a survey

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A Novel Lightweight Algorithm for Sonar Image Recognition

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Prototype-Aligned Federated Learning for Robust Object Extraction in Heterogeneous Remote Sensing

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UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning

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Efficient and Secure GANs: A Survey on Privacy-Preserving and Resource-Aware Models

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Adaptive Strategies for Multi-Class Disease Detection in Azadirachta Indica Using Deep Learning with Few-Shot Adaptation (DL-FSA)

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Complementary-View SAR Target Recognition Based on One-Shot Learning

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Discriminative Feature Enhancement Network for few-shot classification and beyond

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Multi-layer Tuning CLIP for Few-Shot Image Classification

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Few-Shot Classification Study for Prototype Fusion and Completion

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More diversity, less redundancy: Feature refinement network for few-shot SAR image classification

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Evaluation of Few-Shot Learning Algorithms, Training Methods, Backbones and Learning Task for Crack Detection in Manufacturing

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Few-Shot Learning for Triplet-Based EV Energy Consumption Estimation

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An interpretable two-stage adaptive deep learning model for humanitarian aid information prediction and emergency response support

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Few-Shot Fine-Grained Image Classification with Residual Reconstruction Network Based on Feature Enhancement

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A survey of machine learning for estimating workload: considering unknown tasks

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Fused Node-Level Residual Structure Edge Graph Neural Network for Few-Shot Image Classification

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LOFReg: An outlier-based regulariser for deep metric learning

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Few-Shot Learning Method for Space Non-Cooperative Target Recognition

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Supervised Relational Learning with Selective Neighbor Entities for Few-Shot Knowledge Graph Completion

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Unsupervised prototype self-calibration based on hybrid attention contrastive learning for enhanced few-shot action recognition

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On learning discriminative embeddings for optimized top- k matching

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Metric learning for recommendation with conditional generative adversarial networks based hard negative samples

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A detection method for rail internal defects based on data augmentation and lightweight deep network

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VAPCaps: A novel variance-based attention network with imbalance aware loss for better pathology detection in video capsule endoscopy

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Federated Smart Work Package Framework with Triplet Loss for Mental Fatigue Monitoring

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Leveraging CVAE Encoding for Backdoor Attacks in Few-Shot Learning With Prototypical Networks

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Training-Free Few-Shot Image Classification via Kernel Density Estimation with CLIP Embeddings

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Interpretable image classification based on antifactual data

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Temporal Meta-Metric Learning for Multiuser Physical-Layer Authentication in Mobile IIoT

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A few-shot learning approach based on Brownian distance covariance for plant disease classification

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POGP: Probabilistic Genetic Programming With Knowledge Learning for Few-Shot Image Classification

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Ache-Fuzz: Constraint-aware fuzzing for vulnerability discovery in distributed deep learning frameworks

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ATARS: Adaptive task-Aware feature learning for Few-Shot Fine-Grained classification

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Boosting SAR ATR with simulated data: Unsupervised domain adaptation in time, frequency, scattering domains

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Unsupervised deep metric learning based on context and attention weighting

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Intelligent fault diagnosis for elevator door system based on discriminative multi-scale residual network

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Cross-condition few-shot bearing fault diagnosis via learnable diagonal metric and transformer representation

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Learning Structured Distance Mappings for Spacecraft Pose Estimation with Feature Degradation

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Adaptive Multiprototype Gaussian Prototypical Network for Few-Shot UAV Spectrogram Classification

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Noise-Resilient Plasmonic Physical Unclonable Functions via Deep Contrastive Learning

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Computerized Classification Method for Molecular Subtypes in Glioma with Multi-Scale 3D-Attention Branch Networks Analyzing Multi-Sequence Brain MRI Images

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Adaptive similarity-guided self-merging network for few-shot semantic segmentation

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Exploration and Optimization of Lottery Ticket Hypothesis for Few-shot Image Classification Task

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FUSED-Net: Detecting traffic signs with limited data

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Distributed ESP-Now CSI Human Activity Recognition for Few-Shot Energy Saving in Building Automation

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A comprehensive review for Generalized Few-Shot Image Classification

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