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 3291–3300 of 10307 papers

Title	Date	Tasks	Status	Score
A Survey of Incremental Transfer Learning: Combining Peer-to-Peer Federated Learning and Domain Incremental Learning for Multicenter Collaboration	Sep 29, 2023	Continual LearningFederated Learning	CodeCode Available	5
Ensemble Augmentation for Deep Neural Networks Using 1-D Time Series Vibration Data	Aug 6, 2021	Data AugmentationGenerative Adversarial Network	CodeCode Available	5
Early Life Cycle Software Defect Prediction. Why? How?	Nov 26, 2020	PredictionTransfer Learning	CodeCode Available	5
SHERL: Synthesizing High Accuracy and Efficient Memory for Resource-Limited Transfer Learning	Jul 10, 2024	Transfer Learning	CodeCode Available	5
Enhancing Two-Player Performance Through Single-Player Knowledge Transfer: An Empirical Study on Atari 2600 Games	Oct 22, 2024	Atari Gamesreinforcement-learning	CodeCode Available	5
Enriched BERT Embeddings for Scholarly Publication Classification	May 7, 2024	ArticlesClassification	CodeCode Available	5
Ensemble Learning via Knowledge Transfer for CTR Prediction	Nov 25, 2024	Click-Through Rate PredictionEnsemble Learning	CodeCode Available	5
Enhancing textual textbook question answering with large language models and retrieval augmented generation	Feb 5, 2024	Multiple-choiceQuestion Answering	CodeCode Available	5
Enhancing Scene Classification in Cloudy Image Scenarios: A Collaborative Transfer Method with Information Regulation Mechanism using Optical Cloud-Covered and SAR Remote Sensing Images	Jan 8, 2025	Cloud RemovalKnowledge Distillation	CodeCode Available	5
Towards an efficient deep learning model for musical onset detection	Jun 18, 2018	Deep LearningOnset Detection	CodeCode Available	5

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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