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 3941–3950 of 10307 papers

Title	Date	Tasks	Status
Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification-	Oct 15, 2018	General ClassificationLung Disease Classification	—Unverified
Features are fate: a theory of transfer learning in high-dimensional regression	Oct 10, 2024	Transfer Learning	—Unverified
Feature Space Transfer for Data Augmentation	Jan 13, 2018	Data AugmentationDecoder	—Unverified
Feature-Supervised Action Modality Transfer	Aug 6, 2021	Action RecognitionOptical Flow Estimation	—Unverified
Feature Transfer Learning for Deep Face Recognition with Under-Represented Data	Mar 23, 2018	DisentanglementFace Recognition	—Unverified
Feature Transfer Learning for Face Recognition With Under-Represented Data	Jun 1, 2019	DisentanglementFace Recognition	—Unverified
Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification	May 18, 2020	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
FedAL: Black-Box Federated Knowledge Distillation Enabled by Adversarial Learning	Nov 28, 2023	Knowledge DistillationTransfer Learning	—Unverified
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks	Nov 30, 2022	Action RecognitionDomain Adaptation	—Unverified
From Macro to Micro: Boosting micro-expression recognition via pre-training on macro-expression videos	May 26, 2024	Micro Expression RecognitionMicro-Expression Recognition	—Unverified

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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