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 3001–3010 of 10307 papers

Title	Date	Tasks	Status	Hype
FedMEKT: Distillation-based Embedding Knowledge Transfer for Multimodal Federated Learning	Jul 25, 2023	Activity RecognitionFederated Learning	—Unverified	0
Sparse annotation strategies for segmentation of short axis cardiac MRI	Jul 24, 2023	Data AugmentationFew-Shot Learning	—Unverified	0
End-to-End Deep Transfer Learning for Calibration-free Motor Imagery Brain Computer Interfaces	Jul 24, 2023	EEGFeature Engineering	—Unverified	0
NCART: Neural Classification and Regression Tree for Tabular Data	Jul 23, 2023	ClassificationDeep Learning	—Unverified	0
GEM: Boost Simple Network for Glass Surface Segmentation via Vision Foundation Models	Jul 22, 2023	Image Classificationobject-detection	CodeCode Available	1
An X3D Neural Network Analysis for Runner's Performance Assessment in a Wild Sporting Environment	Jul 22, 2023	Action Quality AssessmentAction Recognition	—Unverified	0
Flight Contrail Segmentation via Augmented Transfer Learning with Novel SR Loss Function in Hough Space	Jul 22, 2023	Image SegmentationLine Detection	CodeCode Available	1
Identifying Misinformation on YouTube through Transcript Contextual Analysis with Transformer Models	Jul 22, 2023	ArticlesClassification	CodeCode Available	0
Pick the Best Pre-trained Model: Towards Transferability Estimation for Medical Image Segmentation	Jul 22, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Transfer Learning and Bias Correction with Pre-trained Audio Embeddings	Jul 20, 2023	Information RetrievalInstrument Recognition	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