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 2951–2975 of 10307 papers

TitleStatusHype
Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imagingCode1
Deep Learning Model Transfer in Forest Mapping using Multi-source Satellite SAR and Optical Images—0
Multiscale patch-based feature graphs for image classificationCode0
Weakly Semi-Supervised Detection in Lung Ultrasound Videos—0
Evaluation of a Low-Cost Single-Lead ECG Module for Vascular Ageing Prediction and Studying Smoking-induced Changes in ECG—0
Deep Learning for Steganalysis of Diverse Data Types: A review of methods, taxonomy, challenges and future directions—0
Sparse Array Design for Direction Finding using Deep Learning—0
PMU measurements based short-term voltage stability assessment of power systems via deep transfer learning—0
Segmentation Framework for Heat Loss Identification in Thermal Images: Empowering Scottish Retrofitting and Thermographic Survey Companies—0
Transfer Learning with Partially Observable Offline Data via Causal Bounds—0
RoadScan: A Novel and Robust Transfer Learning Framework for Autonomous Pothole Detection in Roads—0
A Transfer Learning Framework for Proactive Ramp Metering Performance Assessment—0
On-ramp and Off-ramp Traffic Flows Estimation Based on A Data-driven Transfer Learning Framework—0
EventBind: Learning a Unified Representation to Bind Them All for Event-based Open-world Understanding—0
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
One-stage Low-resolution Text Recognition with High-resolution Knowledge TransferCode1
Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control—0
Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across CitiesCode1
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPsCode1
From Fake to Hyperpartisan News Detection Using Domain Adaptation—0
Self-Normalizing Neural Network, Enabling One Shot Transfer Learning for Modeling EDFA Wavelength Dependent Gain—0
Deep Maxout Network-based Feature Fusion and Political Tangent Search Optimizer enabled Transfer Learning for Thalassemia Detection—0
Deep Learning-based Prediction of Stress and Strain Maps in Arterial Walls for Improved Cardiovascular Risk Assessment—0
Curricular Transfer Learning for Sentence Encoded Tasks—0
IndoHerb: Indonesia Medicinal Plants Recognition using Transfer Learning and Deep LearningCode0
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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