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 1361–1370 of 10307 papers

Title	Date	Tasks	Status	Hype
Choquet Integral and Coalition Game-based Ensemble of Deep Learning Models for COVID-19 Screening from Chest X-ray Images	Sep 9, 2021	COVID-19 DiagnosisEnsemble Learning	CodeCode Available	1
ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization	Oct 9, 2020	Cultural Vocal Bursts Intensity PredictionLanguage Modelling	CodeCode Available	1
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer Learning	May 22, 2020	General ClassificationTransfer Learning	CodeCode Available	1
CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision	Dec 14, 2021	Contrastive LearningRepresentation Learning	CodeCode Available	1
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms	Feb 22, 2023	backdoor defenseSelf-Supervised Learning	CodeCode Available	1
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models	May 16, 2020	Graph ClassificationNode Classification	CodeCode Available	1
LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language Models	Nov 11, 2024	Knowledge DistillationLanguage Modeling	CodeCode Available	1
Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort?	Jan 9, 2025	Deep LearningLoad Forecasting	CodeCode Available	1
LogME: Practical Assessment of Pre-trained Models for Transfer Learning	Feb 22, 2021	Model Selectionregression	CodeCode Available	1
Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles	Mar 25, 2021	Domain AdaptationGeometric Matching	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