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

Showing 24262450 of 10307 papers

TitleStatusHype
FOSI: Hybrid First and Second Order OptimizationCode0
From English to Code-Switching: Transfer Learning with Strong Morphological CluesCode0
AMNet: Memorability Estimation with AttentionCode0
FM-OV3D: Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D DetectionCode0
IAI Group at CheckThat! 2024: Transformer Models and Data Augmentation for Checkworthy Claim DetectionCode0
AugWard: Augmentation-Aware Representation Learning for Accurate Graph ClassificationCode0
Cycle-consistent Conditional Adversarial Transfer NetworksCode0
AMLNet: Adversarial Mutual Learning Neural Network for Non-AutoRegressive Multi-Horizon Time Series ForecastingCode0
Fleet Control using Coregionalized Gaussian Process Policy IterationCode0
Flexible Option LearningCode0
Focus on the Positives: Self-Supervised Learning for Biodiversity MonitoringCode0
Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image ClassificationCode0
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer LearningCode0
Augmenting semantic lexicons using word embeddings and transfer learningCode0
First-frame Supervised Video Polyp Segmentation via Propagative and Semantic Dual-teacher NetworkCode0
Adaptive Multi-Task Transfer Learning for Chinese Word Segmentation in Medical TextCode0
Finger Pose Estimation for Under-screen Fingerprint SensorCode0
FissionFusion: Fast Geometric Generation and Hierarchical Souping for Medical Image AnalysisCode0
Augmenting Knowledge Transfer across GraphsCode0
Curriculum Learning for Cumulative Return MaximizationCode0
Fine-Grained Emotion Prediction by Modeling Emotion DefinitionsCode0
Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image SegmentationCode0
CycDA: Unsupervised Cycle Domain Adaptation from Image to VideoCode0
Fine-Grained Classification for Poisonous Fungi Identification with Transfer LearningCode0
Fine-grained Sentiment Classification using BERTCode0
Show:102550
← PrevPage 98 of 413Next →

Benchmark Results

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