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 4391–4400 of 10307 papers

Title	Date	Tasks	Status	Hype
LEAPER: Fast and Accurate FPGA-based System Performance Prediction via Transfer Learning	Aug 22, 2022	Design SynthesisTransfer Learning	—Unverified	0
Dialogue Term Extraction using Transfer Learning and Topological Data Analysis	Aug 22, 2022	Goal-Oriented Dialogue SystemsLanguage Modelling	—Unverified	0
Patient-level Microsatellite Stability Assessment from Whole Slide Images By Combining Momentum Contrast Learning and Group Patch Embeddings	Aug 22, 2022	ClassificationContrastive Learning	CodeCode Available	0
Forensic Dental Age Estimation Using Modified Deep Learning Neural Network	Aug 21, 2022	Age EstimationDeep Learning	—Unverified	0
Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor	Aug 20, 2022	DiagnosticTransfer Learning	—Unverified	0
DenseShift: Towards Accurate and Efficient Low-Bit Power-of-Two Quantization	Aug 20, 2022	QuantizationTransfer Learning	CodeCode Available	1
Atomistic structure search using local surrogate mode	Aug 19, 2022	global-optimizationTransfer Learning	—Unverified	0
Adapting Task-Oriented Dialogue Models for Email Conversations	Aug 19, 2022	Intent DetectionNatural Language Understanding	—Unverified	0
A physics-based domain adaptation framework for modelling and forecasting building energy systems	Aug 19, 2022	Domain Adaptationenergy management	—Unverified	0
Effective Transfer Learning for Low-Resource Natural Language Understanding	Aug 19, 2022	Domain AdaptationNatural Language Understanding	—Unverified	0

Show:10 25 50

← PrevPage 440 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