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

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Showing 1801–1825 of 10307 papers

TitleStatusHype
CromSS: Cross-modal pre-training with noisy labels for remote sensing image segmentation—0
Individual Fairness Through Reweighting and Tuning—0
Diabetic Retinopathy Detection Using Quantum Transfer Learning—0
KITE: A Kernel-based Improved Transferability Estimation Method—0
Transformer-Based Self-Supervised Learning for Histopathological Classification of Ischemic Stroke Clot Origin—0
Employing Federated Learning for Training Autonomous HVAC Systems—0
Koopman-based Deep Learning for Nonlinear System Estimation—0
Self-supervised Pre-training of Text RecognizersCode0
Why does Knowledge Distillation Work? Rethink its Attention and Fidelity MechanismCode0
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents—0
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning—0
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray ClassificationCode0
What Drives Performance in Multilingual Language Models?Code0
Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing ImagesCode0
Generation of Uncorrelated Residual Variables for Chemical Process Fault Diagnosis via Transfer Learning-based Input-Output Decoupled Network—0
Task and Domain Adaptive Reinforcement Learning for Robot ControlCode0
Transfer Learning and Transformer Architecture for Financial Sentiment Analysis—0
Enhancing Action Recognition from Low-Quality Skeleton Data via Part-Level Knowledge Distillation—0
Efficient Remote Sensing with Harmonized Transfer Learning and Modality AlignmentCode2
Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text MatchingCode1
EkoHate: Abusive Language and Hate Speech Detection for Code-switched Political Discussions on Nigerian TwitterCode0
Remote Sensing Image Enhancement through Spatiotemporal Filtering—0
Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering—0
Toxicity Classification in Ukrainian—0
Knowledge Transfer for Cross-Domain Reinforcement Learning: A Systematic Review—0
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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