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 2231–2240 of 10307 papers

Title	Date	Tasks	Status	Score
GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer Learning	May 7, 2021	Transfer Learning	CodeCode Available	5
GAN pretraining for deep convolutional autoencoders applied to Software-based Fingerprint Presentation Attack Detection	May 21, 2021	Transfer Learning	CodeCode Available	5
Gated Domain Units for Multi-source Domain Generalization	Jun 24, 2022	Domain GeneralizationTransfer Learning	CodeCode Available	5
An easy zero-shot learning combination: Texture Sensitive Semantic Segmentation IceHrNet and Advanced Style Transfer Learning Strategy	Sep 30, 2023	DecoderSegmentation	CodeCode Available	5
Gammatonegram Representation for End-to-End Dysarthric Speech Processing Tasks: Speech Recognition, Speaker Identification, and Intelligibility Assessment	Jul 6, 2023	Speaker Identificationspeech-recognition	CodeCode Available	5
Fuzzy Rank-based Fusion of CNN Models using Gompertz Function for Screening COVID-19 CT-Scans	Jul 8, 2021	Image ClassificationTransfer Learning	CodeCode Available	5
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation	Aug 4, 2024	Causal InferenceTransfer Learning	CodeCode Available	5
GAN Cocktail: mixing GANs without dataset access	Jun 7, 2021	Transfer Learning	CodeCode Available	5
Generalizing Teacher Networks for Effective Knowledge Distillation Across Student Architectures	Jul 22, 2024	Knowledge DistillationModel Compression	CodeCode Available	5
GKT: A Novel Guidance-Based Knowledge Transfer Framework For Efficient Cloud-edge Collaboration LLM Deployment	May 30, 2024	GSM8KKnowledge Distillation	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