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 1881–1890 of 10307 papers

Title	Date	Tasks	Status	Score
Intracerebral EEG Artifact Identification Using Convolutional Neural Networks	Aug 13, 2018	Artifact DetectionEEG	CodeCode Available	5
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage Perspective	Feb 26, 2025	Computational EfficiencyTransfer Learning	CodeCode Available	5
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks	Oct 3, 2019	Few-Shot Image ClassificationGeneral Classification	CodeCode Available	5
HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection	Jan 22, 2021	Hate Speech DetectionTransfer Learning	CodeCode Available	5
Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning	Jun 7, 2019	Few-Shot LearningGeneralized Few-Shot Learning	CodeCode Available	5
Hardware Conditioned Policies for Multi-Robot Transfer Learning	Nov 24, 2018	Deep Reinforcement LearningIndustrial Robots	CodeCode Available	5
Can Modifying Data Address Graph Domain Adaptation?	Jul 27, 2024	Domain AdaptationGRAPH DOMAIN ADAPTATION	CodeCode Available	5
Harnessing multiple LLMs for Information Retrieval: A case study on Deep Learning methodologies in Biodiversity publications	Nov 14, 2024	Information RetrievalRAG	CodeCode Available	5
HCR-Net: A deep learning based script independent handwritten character recognition network	Aug 15, 2021	Image AugmentationTransfer Learning	CodeCode Available	5
HANA: A HAndwritten NAme Database for Offline Handwritten Text Recognition	Jan 22, 2021	Handwritten Text RecognitionTransfer Learning	CodeCode Available	5

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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