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 7851–7900 of 10307 papers

TitleStatusHype
Learning to Ask Screening Questions for Job Postings—0
Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings—0
Investigating Transferability in Pretrained Language ModelsCode0
Transfer Learning for Thermal Comfort Prediction in Multiple Cities—0
UDapter: Language Adaptation for Truly Universal Dependency ParsingCode1
Video Contents Understanding using Deep Neural Networks—0
Meta-Transfer Learning for Code-Switched Speech RecognitionCode1
Deepfake Video Forensics based on Transfer Learning—0
Deep Transfer Learning For Plant Center Localization—0
A Cognition-Affect Integrated Model of Emotion—0
Extending Multilingual BERT to Low-Resource Languages—0
Meta-Learning for Few-Shot Land Cover Classification—0
Heterogeneous Representation Learning: A Review—0
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XLCode1
UXLA: A Robust Unsupervised Data Augmentation Framework for Zero-Resource Cross-Lingual NLP—0
KACC: A Multi-task Benchmark for Knowledge Abstraction, Concretization and CompletionCode1
Transfer Learning for sEMG-based Hand Gesture Classification using Deep Learning in a Master-Slave Architecture—0
A scoping review of transfer learning research on medical image analysis using ImageNet—0
Omnidirectional Transfer for Quasilinear Lifelong LearningCode1
Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less ForgettingCode1
CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documentsCode2
Station-to-User Transfer Learning: Towards Explainable User Clustering Through Latent Trip Signatures Using Tidal-Regularized Non-Negative Matrix Factorization—0
Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection SegmentationCode1
A knowledge transfer model for COVID-19 predicting and non-pharmaceutical intervention simulation—0
Federated Transfer Learning for EEG Signal ClassificationCode1
Cross-Domain Structure Preserving Projection for Heterogeneous Domain AdaptationCode1
Joint Liver Lesion Segmentation and Classification via Transfer Learning—0
On the Limits to Multi-Modal Popularity Prediction on Instagram -- A New Robust, Efficient and Explainable Baseline—0
Fashionpedia: Ontology, Segmentation, and an Attribute Localization DatasetCode1
Development of a High Fidelity Simulator for Generalised Photometric Based Space Object Classification using Machine Learning—0
KrakN: Transfer Learning framework for thin crack detection in infrastructure maintenanceCode1
AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer LearningCode1
A Survey on Incorporating Domain Knowledge into Deep Learning for Medical Image Analysis—0
On the safety of vulnerable road users by cyclist orientation detection using Deep Learning—0
How Much Off-The-Shelf Knowledge Is Transferable From Natural Images To Pathology Images?—0
New Protocols and Negative Results for Textual Entailment Data CollectionCode1
Data Annealing for Informal Language Understanding Tasks—0
Explicit Domain Adaptation with Loosely Coupled Samples—0
Sparse Array Selection Across Arbitrary Sensor Geometries with Deep Transfer Learning—0
A survey on domain adaptation theory: learning bounds and theoretical guarantees—0
Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization—0
Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networksCode0
Learning Constrained Dynamics with Gauss Principle adhering Gaussian ProcessesCode0
Learning context-aware structural representations to predict antigen and antibody binding interfacesCode1
Per-pixel Classification Rebar Exposures in Bridge Eye-inspection—0
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning—0
Deep Learning for Screening COVID-19 using Chest X-Ray Images—0
Chip Placement with Deep Reinforcement LearningCode1
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors—0
Headless Horseman: Adversarial Attacks on Transfer Learning Models—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