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 3961–3970 of 10307 papers

Title	Date	Tasks	Status	Hype
Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs	Nov 29, 2022	Knowledge GraphsTransfer Learning	CodeCode Available	1
Transferability Estimation Based On Principal Gradient Expectation	Nov 29, 2022	Transfer Learning	—Unverified	0
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation	Nov 28, 2022	Image RegistrationSynthetic Data Generation	CodeCode Available	0
Reinforced Genetic Algorithm for Structure-based Drug Design	Nov 28, 2022	Combinatorial OptimizationDrug Design	CodeCode Available	1
Higher-order Knowledge Transfer for Dynamic Community Detection with Great Changes	Nov 28, 2022	Community DetectionDynamic Community Detection	—Unverified	0
Hypernetworks for Zero-shot Transfer in Reinforcement Learning	Nov 28, 2022	continuous-controlContinuous Control	—Unverified	0
Learning to Learn: How to Continuously Teach Humans and Machines	Nov 28, 2022	class-incremental learningClass Incremental Learning	—Unverified	0
Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis	Nov 28, 2022	Binary Classificationimage-classification	—Unverified	0
Inapplicable Actions Learning for Knowledge Transfer in Reinforcement Learning	Nov 28, 2022	reinforcement-learningReinforcement Learning	—Unverified	0
Automated Detection of Dolphin Whistles with Convolutional Networks and Transfer Learning	Nov 28, 2022	ManagementTransfer Learning	—Unverified	0

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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