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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 3801–3810 of 10307 papers

Title	Date	Tasks	Status
AMLNet: Adversarial Mutual Learning Neural Network for Non-AutoRegressive Multi-Horizon Time Series Forecasting	Oct 30, 2023	DecoderDiversity	CodeCode Available
Adapter Pruning using Tropical Characterization	Oct 30, 2023	Language ModelingLanguage Modelling	—Unverified
A foundational neural operator that continuously learns without forgetting	Oct 29, 2023	Operator learningTransfer Learning	—Unverified
RCKD: Response-Based Cross-Task Knowledge Distillation for Pathological Image Analysis	Oct 29, 2023	Image ClassificationKnowledge Distillation	—Unverified
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning	Oct 29, 2023	Deep Reinforcement Learningreinforcement-learning	—Unverified
Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System	Oct 29, 2023	Demand Forecastingenergy management	—Unverified
A transfer learning approach with convolutional neural network for Face Mask Detection	Oct 29, 2023	Transfer Learning	—Unverified
QWID: Quantized Weed Identification Deep neural network	Oct 29, 2023	QuantizationTransfer Learning	CodeCode Available
ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object Detection	Oct 28, 2023	3D Object DetectionAutonomous Driving	CodeCode Available
MELEP: A Novel Predictive Measure of Transferability in Multi-Label ECG Diagnosis	Oct 27, 2023	ECG ClassificationElectrocardiography (ECG)	CodeCode Available

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All datasets Office-Home 100 sleep nights of 8 caregivers BanglaLekha Isolated Dataset COCO70 KITTI Object Tracking Evaluation 2012 Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	APCLIP	Accuracy	84.2	—	Unverified
2	DFA-ENT	Accuracy	69.2	—	Unverified
3	DFA-SAFN	Accuracy	69.1	—	Unverified
4	EasyTL	Accuracy	63.3	—	Unverified
5	MEDA	Accuracy	60.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	10-20% Mask PSNR	3.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Chatterjee, Dutta et al.[1]	Accuracy	96.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Co-Tuning	Accuracy	85.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Physical Access	EER	5.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	riadd.aucmedi	AUROC	0.95	—	Unverified