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 9376–9400 of 10307 papers

TitleStatusHype
Facial Emotion Recognition Under Mask Coverage Using a Data Augmentation TechniqueCode0
Facial Expression Recognition Under Partial Occlusion from Virtual Reality Headsets based on Transfer LearningCode0
Facial Landmark Predictions with Applications to MetaverseCode0
Facilitating the sharing of electrophysiology data analysis results through in-depth provenance captureCode0
E-Sort: Empowering End-to-end Neural Network for Multi-channel Spike Sorting with Transfer Learning and Fast Post-processingCode0
Fair Generative Models via Transfer LearningCode0
fairseq S2T: Fast Speech-to-Text Modeling with fairseqCode0
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained ModelCode0
Farewell Freebase: Migrating the SimpleQuestions Dataset to DBpediaCode0
Fast Enhanced CT Metal Artifact Reduction using Data Domain Deep LearningCode0
Fast deep learning correspondence for neuron tracking and identification in C.elegans using synthetic trainingCode0
Faster Reinforcement Learning Using Active SimulatorsCode0
Fast Solar Image Classification Using Deep Learning and its Importance for Automation in Solar PhysicsCode0
FBDNN: Filter Banks and Deep Neural Networks for Portable and Fast Brain-Computer InterfacesCode0
FBK-DH at SemEval-2020 Task 12: Using Multi-channel BERT for Multilingual Offensive Language DetectionCode0
Feature-Based Transfer Learning for Network SecurityCode0
Multi-modal Speech Emotion Recognition via Feature Distribution Adaptation NetworkCode0
An Embarrassingly Simple Approach for Knowledge DistillationCode0
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated LearningCode0
Federated Continual Graph LearningCode0
Federated Continual Learning for Text Classification via Selective Inter-client TransferCode0
Federated Domain Generalization via Prompt Learning and AggregationCode0
Federated Machine Learning: Concept and ApplicationsCode0
FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain RecommendationCode0
Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things ApplicationCode0
Show:102550
← PrevPage 376 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