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 1271–1280 of 10307 papers

TitleStatusHype
Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative StudyCode0
Assessing Large Language Models for Online Extremism Research: Identification, Explanation, and New Knowledge—0
On Transfer Learning for a Fully Convolutional Deep Neural SIMO Receiver—0
Data Quality Monitoring through Transfer Learning on Anomaly Detection for the Hadron Calorimeters—0
Efficient Transfer Learning Framework for Cross-Domain Click-Through Rate Prediction—0
Adaptive Sample Aggregation In Transfer Learning—0
Auxiliary Input in Training: Incorporating Catheter Features into Deep Learning Models for ECG-Free Dynamic Coronary Roadmapping—0
Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection—0
Emulating Brain-like Rapid Learning in Neuromorphic Edge ComputingCode0
Q-MRS: A Deep Learning Framework for Quantitative Magnetic Resonance Spectra Analysis—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