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 351–375 of 10307 papers

TitleStatusHype
Exploring Cultural Nuances in Emotion Perception Across 15 African Languages—0
FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust FusionCode0
The Coralscapes Dataset: Semantic Scene Understanding in Coral ReefsCode1
Untangling the Influence of Typology, Data and Model Architecture on Ranking Transfer Languages for Cross-Lingual POS Tagging—0
Optimizing Breast Cancer Detection in Mammograms: A Comprehensive Study of Transfer Learning, Resolution Reduction, and Multi-View Classification—0
Anomaly Detection Using Computer Vision: A Comparative Analysis of Class Distinction and Performance Metrics—0
Continual Reinforcement Learning for HVAC Systems Control: Integrating Hypernetworks and Transfer LearningCode0
Pitch Contour Exploration Across Audio Domains: A Vision-Based Transfer Learning Approach—0
PAD: Towards Efficient Data Generation for Transfer Learning Using Phrase Alignment—0
Enhancing Dataset Distillation via Non-Critical Region RefinementCode0
k-NN as a Simple and Effective Estimator of Transferability—0
PNN: A Novel Progressive Neural Network for Fault Classification in Rotating Machinery under Small Dataset Constraint—0
Feature Calibration enhanced Parameter Synthesis for CLIP-based Class-incremental Learning—0
Natural Language Processing for Electronic Health Records in Scandinavian Languages: Norwegian, Swedish, and Danish—0
Efficient Continual Adaptation of Pretrained Robotic Policy with Online Meta-Learned Adapters—0
FedSKD: Aggregation-free Model-heterogeneous Federated Learning using Multi-dimensional Similarity Knowledge Distillation—0
Training A Neural Network For Partially Occluded Road Sign Identification In The Context Of Autonomous Vehicles—0
Cross-Domain Underwater Image Enhancement Guided by No-Reference Image Quality Assessment: A Transfer Learning Approach—0
Adaptive Physics-informed Neural Networks: A Survey—0
Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization—0
Physics-Guided Multi-Fidelity DeepONet for Data-Efficient Flow Field Prediction—0
Automated diagnosis of lung diseases using vision transformer: a comparative study on chest x-ray classification—0
Causal Inference based Transfer Learning with LLMs: An Efficient Framework for Industrial RUL Prediction—0
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation—0
Efficient Deployment of Deep MIMO Detection Using Learngene—0
Show:102550
← PrevPage 15 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