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 1231–1240 of 10307 papers

Title	Date	Tasks	Status	Hype
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes	Sep 15, 2020	Deep LearningDescriptive	CodeCode Available	1
Critical Thinking for Language Models	Sep 15, 2020	Transfer Learningvalid	CodeCode Available	1
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization	Sep 11, 2020	Knowledge GraphsTransfer Learning	CodeCode Available	1
Transfer Graph Neural Networks for Pandemic Forecasting	Sep 10, 2020	Meta-LearningRepresentation Learning	CodeCode Available	1
Anonymization of labeled TOF-MRA images for brain vessel segmentation using generative adversarial networks	Sep 9, 2020	Medical Image AnalysisTransfer Learning	CodeCode Available	1
Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity	Sep 6, 2020	NMTTransfer Learning	CodeCode Available	1
Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT	Sep 5, 2020	Lesion DetectionPartially Labeled Datasets	CodeCode Available	1
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning	Sep 4, 2020	ClassificationClustering	CodeCode Available	1
AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning	Sep 3, 2020	BIG-bench Machine LearningTransfer Learning	CodeCode Available	1
Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading	Sep 2, 2020	automatic short answer gradingTransfer Learning	CodeCode Available	1

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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