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 4521–4530 of 10307 papers

Title	Date	Tasks	Status	Hype
The Power of Transfer Learning in Agricultural Applications: AgriNet	Jul 8, 2022	Face RecognitionTransfer Learning	—Unverified	0
An Embedding-Dynamic Approach to Self-supervised Learning	Jul 7, 2022	Classificationimage-classification	—Unverified	0
G2L: A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning	Jul 7, 2022	Transfer Learning	—Unverified	0
Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning	Jul 7, 2022	Automatic Modulation RecognitionRepresentation Learning	—Unverified	0
Deep learning based Hand gesture recognition system and design of a Human-Machine Interface	Jul 7, 2022	Gesture RecognitionHand Detection	—Unverified	0
PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape Recognition	Jul 7, 2022	3D Shape Classification3D Shape Recognition	CodeCode Available	1
Lightweight Encoder-Decoder Architecture for Foot Ulcer Segmentation	Jul 6, 2022	DecoderSegmentation	—Unverified	0
Low-resource Low-footprint Wake-word Detection using Knowledge Distillation	Jul 6, 2022	Knowledge Distillationspeech-recognition	—Unverified	0
Distillation to Enhance the Portability of Risk Models Across Institutions with Large Patient Claims Database	Jul 6, 2022	Readmission PredictionTransfer Learning	—Unverified	0
Pre-training Transformers for Molecular Property Prediction Using Reaction Prediction	Jul 6, 2022	Drug DiscoveryMolecular Property Prediction	—Unverified	0

Show:10 25 50

← PrevPage 453 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