mlsanityData to 7 Oct 2026

Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification

arXiv 2411.12151 ↗First posted 19 Nov 2024cs.CVcited by 11

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Abstract (arXiv)

This study aims to optimize the few-shot image classification task and improve the model's feature extraction and classification performance by combining self-supervised learning with the deep network model ResNet-101. During the training process, we first pre-train the model with self-supervision to enable it to learn common feature expressions on a large amount of unlabeled data; then fine-tune it on the few-shot dataset Mini-ImageNet to improve the model's accuracy and generalization ability under limited data. The experimental results show that compared with traditional convolutional neural networks, ResNet-50, DenseNet, and other models, our method has achieved excellent performance of about 95.12% in classification accuracy (ACC) and F1 score, verifying the effectiveness of self-supervised learning in few-shot classification. This method provides an efficient and reliable solution for the field of few-shot image classification.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 21 of its 32 references that are in the map. First posted on arXiv 19 Nov 2024.

Builds on

21 of 32 references.

References · 21

  1. 2024Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Miningcited by 47
  2. 2024Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networkscited by 33
  3. 2024Dynamic Fraud Detection: Integrating Reinforcement Learning into Graph Neural Networkscited by 19
  4. 2024Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learningcited by 17
  5. 2024Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visitscited by 12
  6. 2024A Lightweight GAN-Based Image Fusion Algorithm for Visible and Infrared Imagescited by 11
  7. 2024Wasserstein Distance-Weighted Adversarial Network for Cross-Domain Credit Risk Assessmentcited by 11
  8. 2024Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithmcited by 11
  9. 2024Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithmcited by 11
  10. 2024Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentationcited by 10
  11. 2024Unveiling the Potential of Graph Neural Networks in SME Credit Risk Assessmentcited by 9
  12. 2024Applying Hybrid Graph Neural Networks to Strengthen Credit Risk Analysiscited by 8
9 more
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  2. 2024Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Studycited by 8
  3. 2024Convolutional Neural Networks for Predictive Modeling of Lung Diseasecited by 7
  4. 2024Automated Genre-Aware Article Scoring and Feedback Using Large Language Modelscited by 7
  5. 2024Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysiscited by 7
  6. 2024Deep Learning-Based Channel Squeeze U-Structure for Lung Nodule Detection and Segmentationcited by 6
  7. 2024Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Managementcited by 6
  8. 2024Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detectioncited by 5
  9. 2024Optimizing Retrieval-Augmented Generation with Elasticsearch for Enhanced Question-Answering Systemscited by 5

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Cited by year

Citing papers per year: 2024: 11.

11 papers.

  1. 2024Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Trainingcited by 13
  2. 2024An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reductioncited by 9
  3. 2024Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Datacited by 7
  4. 2024Accurate Medical Named Entity Recognition Through Specialized NLP Modelscited by 7
  5. 2024Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Modelscited by 6
  6. 2024Dynamic Scheduling Strategies for Resource Optimization in Computing Environmentscited by 6
  7. 2024Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothingcited by 5
  8. 2024Optimizing Multi-Task Learning for Enhanced Performance in Large Language Modelscited by 5
  9. 2024Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXtcited by 5
  10. 2024Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Datacited by 3
  11. 2024Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoderscited by 2