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 2776–2800 of 10307 papers

TitleStatusHype
Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO—0
Deep Learning for Computational Cytology: A Survey—0
Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review—0
Deep Transfer Learning-Assisted Signal Detection for Ambient Backscatter Communications—0
Baselines for Reinforcement Learning in Text Games—0
Deep Transfer Learning Based Intrusion Detection System for Electric Vehicular Networks—0
Deep Transfer Learning Based Peer Review Aggregation and Meta-review Generation for Scientific Articles—0
Auto-Transfer: Learning to Route Transferable Representations—0
A Comparison of Self-Supervised Pretraining Approaches for Predicting Disease Risk from Chest Radiograph Images—0
An Audio-Based Fault Diagnosis Method for Quadrotors Using Convolutional Neural Network and Transfer Learning—0
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization—0
Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification—0
Deep Transfer Learning for Cross-domain Activity Recognition—0
Deep Learning for Bias Detection: From Inception to Deployment—0
Deep Transfer Learning for EEG-based Brain Computer Interface—0
Deep Transfer Learning for Error Decoding from Non-Invasive EEG—0
Deep Transfer Learning for Few-Shot SAR Image Classification—0
Deep Transfer Learning for Identifications of Slope Surface Cracks—0
Deep transfer learning for image classification: a survey—0
Deep transfer learning for improving single-EEG arousal detection—0
Deep Transfer Learning for Industrial Automation: A Review and Discussion of New Techniques for Data-Driven Machine Learning—0
Deep Transfer Learning for Infectious Disease Case Detection Using Electronic Medical Records—0
Deep Transfer Learning for Intelligent Vehicle Perception: a Survey—0
Deep Transfer Learning for Kidney Cancer Diagnosis—0
Δ-Patching: A Framework for Rapid Adaptation of Pre-trained Convolutional Networks without Base Performance Loss—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