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 8451–8475 of 10307 papers

TitleStatusHype
Zero-Shot Task TransferCode0
Transferring climate change physical knowledgeCode0
Towards More Accurate Automatic Sleep Staging via Deep Transfer LearningCode0
Multi-Source Cross-Lingual Model Transfer: Learning What to ShareCode0
Transferring Confluent Knowledge to Argument MiningCode0
Transferable Clean-Label Poisoning Attacks on Deep Neural NetsCode0
Transfer Learning of Artist Group Factors to Musical Genre ClassificationCode0
WikiBERT models: deep transfer learning for many languagesCode0
Unsupervised Domain Adaptation with Progressive Adaptation of SubspacesCode0
Transfer learning approach to Classify the X-ray image that corresponds to corona disease Using ResNet50 pretrained by ChexNetCode0
Transferring facade labels between point clouds with semantic octrees while considering change detectionCode0
XNLIeu: a dataset for cross-lingual NLI in BasqueCode0
Transfer learning method in the problem of binary classification of chest X-raysCode0
Unsupervised Image Classification for Deep Representation LearningCode0
XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic ParsingCode0
Transferable Class-Modelling for Decentralized Source Attribution of GAN-Generated ImagesCode0
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern RecognitionCode0
Transfer Learning Approach to Bicycle-sharing Systems' Station Location Planning using OpenStreetMap DataCode0
Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice ModelsCode0
Transfer Learning and the Early Estimation of Single-Photon Source Quality using Machine Learning MethodsCode0
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain AdaptationCode0
Wildfire danger prediction optimization with transfer learningCode0
XSemPLR: Cross-Lingual Semantic Parsing in Multiple Natural Languages and Meaning RepresentationsCode0
To Share or not to Share: Predicting Sets of Sources for Model Transfer LearningCode0
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork PromptCode0
Show:102550
← PrevPage 339 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