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 1051–1075 of 10307 papers

TitleStatusHype
Water quality polluted by total suspended solids classified within an Artificial Neural Network approach—0
Explainable AI in Handwriting Detection for Dyslexia Using Transfer Learning—0
A novel approach towards the classification of Bone Fracture from Musculoskeletal Radiography images using Attention Based Transfer Learning—0
Effects of Soft-Domain Transfer and Named Entity Information on Deception Detection—0
Transfer Learning on Transformers for Building Energy Consumption Forecasting -- A Comparative Study—0
ST-MoE-BERT: A Spatial-Temporal Mixture-of-Experts Framework for Long-Term Cross-City Mobility PredictionCode1
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning—0
Transfer Reinforcement Learning in Heterogeneous Action Spaces using Subgoal Mapping—0
How Does Data Diversity Shape the Weight Landscape of Neural Networks?—0
IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI—0
CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence—0
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning—0
TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent CollaborationCode1
Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling—0
iFuzzyTL: Interpretable Fuzzy Transfer Learning for SSVEP BCI System—0
Tracking Universal Features Through Fine-Tuning and Model Merging—0
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators—0
TAS: Distilling Arbitrary Teacher and Student via a Hybrid Assistant—0
Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis—0
Exploring transfer learning for Deep NLP systems on rarely annotated languages—0
Learning to rumble: Automated elephant call classification, detection and endpointing using deep architectures—0
Transfer Learning Adapts to Changing PSD in Gravitational Wave Data—0
A Survey on Deep Tabular Learning—0
YOLO-ELA: Efficient Local Attention Modeling for High-Performance Real-Time Insulator Defect Detection—0
Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptations—0
Show:102550
← PrevPage 43 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