SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9151–9175 of 10307 papers

TitleStatusHype
Knowledge Distillation with Deep SupervisionCode0
Deep Metric Transfer for Label Propagation with Limited Annotated DataCode0
Deep Model Transferability from Attribution MapsCode0
Deep Neural Network Fingerprinting by Conferrable Adversarial ExamplesCode0
Deep Neural Networks Under StressCode0
Deep Nonparametric Conditional Independence Tests for ImagesCode0
Deep Optimal Transport for Domain Adaptation on SPD ManifoldsCode0
DeepPavlov at SemEval-2024 Task 8: Leveraging Transfer Learning for Detecting Boundaries of Machine-Generated TextsCode0
Deep Reference Priors: What is the best way to pretrain a model?Code0
Deep Reinforcement Learning: An OverviewCode0
Deep Residual Network based Automatic Image Grading for Diabetic Macular EdemaCode0
Deep Transfer Learning Based Downlink Channel Prediction for FDD Massive MIMO SystemsCode0
Deep Transfer Learning for Automated Diagnosis of Skin Lesions from PhotographsCode0
Deep Transfer Learning for Multiple Class Novelty DetectionCode0
Deep Transfer Learning for Multi-source Entity Linkage via Domain AdaptationCode0
Deep Transfer Learning for Source Code ModelingCode0
Deep Transfer Learning for Static Malware ClassificationCode0
Deep transfer learning for visual analysis and attribution of paintings by RaphaelCode0
Deep transfer learning in the assessment of the quality of protein modelsCode0
Deep transfer learning method based on automatic domain alignment and moment matchingCode0
Deep Transfer Reinforcement Learning for Text SummarizationCode0
Deep UL2DL: Channel Knowledge Transfer from Uplink to DownlinkCode0
Global Neural Networks and The Data Scaling Effect in Financial Time Series ForecastingCode0
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and GeometryCode0
DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech DetectionCode0
Show:102550
← PrevPage 367 of 413Next →
All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified