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 9826–9850 of 10307 papers

TitleStatusHype
Transfer learning from synthetic to real images using variational autoencoders for robotic applications—0
N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning—0
Object Recognition from very few Training Examples for Enhancing Bicycle Maps—0
Long-Term Ensemble Learning of Visual Place Classifiers—0
Multi-Label Zero-Shot Human Action Recognition via Joint Latent Ranking Embedding—0
Shapechanger: Environments for Transfer LearningCode0
Viewpoint Invariant Action Recognition using RGB-D Videos—0
Unsupervised state representation learning with robotic priors: a robustness benchmark—0
Shared Learning : Enhancing Reinforcement in Q-Ensembles—0
Deep Learning for Automatic Stereotypical Motor Movement Detection using Wearable Sensors in Autism Spectrum Disorders—0
Empower Sequence Labeling with Task-Aware Neural Language ModelCode0
Model Distillation with Knowledge Transfer from Face Classification to Alignment and Verification—0
Optimal Transport for Deep Joint Transfer Learning—0
How to Train a CAT: Learning Canonical Appearance Transformations for Direct Visual Localization Under Illumination ChangeCode0
Best Practices in Convolutional Networks for Forward-Looking Sonar Image Recognition—0
Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory AnalysisCode0
Group-level Emotion Recognition using Transfer Learning from Face IdentificationCode0
The Devil is in the Tails: Fine-grained Classification in the Wild—0
Knowledge Transfer Between Artificial Intelligence Systems—0
Cross-Lingual Transfer Learning for POS Tagging without Cross-Lingual Resources—0
Neural Paraphrase Generation using Transfer Learning—0
NITE: A Neural Inductive Teaching Framework for Domain Specific NER—0
Exploring Cross-Lingual Transfer of Morphological Knowledge In Sequence-to-Sequence Models—0
``Deep'' Learning : Detecting Metaphoricity in Adjective-Noun Pairs—0
A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community—0
Show:102550
← PrevPage 394 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