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 2321–2330 of 10307 papers

Title	Date	Tasks	Status	Score
A comparison of small sample methods for Handshape Recognition	Apr 1, 2023	Hand Gesture RecognitionMeta-Learning	CodeCode Available	5
Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer Learning	Oct 12, 2019	Autonomous NavigationDeep Reinforcement Learning	CodeCode Available	5
FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations	May 17, 2020	Data AugmentationGeneral Classification	CodeCode Available	5
Funnelling: A New Ensemble Method for Heterogeneous Transfer Learning and its Application to Cross-Lingual Text Classification	Jan 31, 2019	AllClassification	CodeCode Available	5
Understanding the Transferability of Representations via Task-Relatedness	Jul 3, 2023	Transfer Learning	CodeCode Available	5
From Video Game to Real Robot: The Transfer between Action Spaces	May 2, 2019	Deep Reinforcement LearningReinforcement Learning	CodeCode Available	5
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents	Apr 11, 2023	Decision MakingQ-Learning	CodeCode Available	5
From Colors to Classes: Emergence of Concepts in Vision Transformers	Mar 31, 2025	Domain AdaptationTransfer Learning	CodeCode Available	5
From English to Code-Switching: Transfer Learning with Strong Morphological Clues	Sep 11, 2019	Language IdentificationNamed Entity Recognition (NER)	CodeCode Available	5
FrImCla: A Framework for Image Classification Using Traditional and Transfer Learning Techniques	Mar 13, 2020	ClassificationCPU	CodeCode Available	5

Show:10 25 50

← PrevPage 233 of 1031Next →

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