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 751–775 of 10307 papers

Title	Date	Tasks	Status	Hype	Score
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning	Jan 6, 2020	General ClassificationTransfer Learning	CodeCode Available	1	5
An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysis	Jun 17, 2021	Transfer Learning	CodeCode Available	1	5
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer Learning	May 22, 2020	General ClassificationTransfer Learning	CodeCode Available	1	5
An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature Selection	Dec 17, 2022	feature selectionTransfer Learning	CodeCode Available	1	5
A Broader Study of Cross-Domain Few-Shot Learning	Dec 16, 2019	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1	5
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise	Nov 20, 2017	ClassificationGeneral Classification	CodeCode Available	1	5
Class-relation Knowledge Distillation for Novel Class Discovery	Jul 18, 2023	Knowledge DistillationNovel Class Discovery	CodeCode Available	1	5
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks	Aug 14, 2022	Few-Shot LearningNode Classification	CodeCode Available	1	5
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks	Jun 18, 2022	Continual LearningTransfer Learning	CodeCode Available	1	5
A New Knowledge Distillation Network for Incremental Few-Shot Surface Defect Detection	Sep 1, 2022	Defect DetectionKnowledge Distillation	CodeCode Available	1	5
CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision	Dec 14, 2021	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
Deep Transferring Quantization	Aug 1, 2020	Face Recognitionimage-classification	CodeCode Available	1	5
aschern at SemEval-2020 Task 11: It Takes Three to Tango: RoBERTa, CRF, and Transfer Learning	Aug 6, 2020	ArticlesTransfer Learning	CodeCode Available	1	5
CLIP-VG: Self-paced Curriculum Adapting of CLIP for Visual Grounding	May 15, 2023	DiversityTransfer Learning	CodeCode Available	1	5
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching	Oct 1, 2020	Deep LearningTransfer Learning	CodeCode Available	1	5
Graph Contrastive Learning with Augmentations	Oct 22, 2020	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
Denoised Self-Augmented Learning for Social Recommendation	May 22, 2023	Self-Supervised LearningTransfer Learning	CodeCode Available	1	5
CODE-CL: Conceptor-Based Gradient Projection for Deep Continual Learning	Nov 21, 2024	Continual LearningImage Classification	CodeCode Available	1	5
CODE-AE: A Coherent De-confounding Autoencoder for Predicting Patient-Specific Drug Response From Cell Line Transcriptomics	Jan 31, 2021	Transfer Learning	CodeCode Available	1	5
Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks	Mar 25, 2022	Incremental LearningKnowledge Distillation	CodeCode Available	1	5
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy	Nov 15, 2023	ClassificationDiversity	CodeCode Available	1	5
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing	Apr 6, 2021	API Sequence RecommendationCode Comment Generation	CodeCode Available	1	5
Grounding Psychological Shape Space in Convolutional Neural Networks	Nov 16, 2021	Multi-Task LearningTransfer Learning	CodeCode Available	1	5
GroupContrast: Semantic-aware Self-supervised Representation Learning for 3D Understanding	Mar 14, 2024	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
Densely Guided Knowledge Distillation using Multiple Teacher Assistants	Sep 18, 2020	Knowledge DistillationModel Compression	CodeCode Available	1	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