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 1021–1030 of 10307 papers

Title	Date	Tasks	Status	Hype	Score
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities	Feb 8, 2022	Domain AdaptationGraph Mining	CodeCode Available	1	5
Pan-Cancer Computational Histopathology (PC-CHiP) analysis using deep learning	Jul 27, 2020	Deep LearningDiagnostic	CodeCode Available	1	5
Efficient Few-Shot Object Detection via Knowledge Inheritance	Mar 23, 2022	Few-Shot Object DetectionObject	CodeCode Available	1	5
Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters	Feb 1, 2024	Mixture-of-Expertsparameter-efficient fine-tuning	CodeCode Available	1	5
Audio Spoofing Verification using Deep Convolutional Neural Networks by Transfer Learning	Aug 8, 2020	Speaker VerificationTransfer Learning	CodeCode Available	1	5
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation	Jun 6, 2020	Activity RecognitionDeep Learning	CodeCode Available	1	5
Benchmarking and scaling of deep learning models for land cover image classification	Nov 18, 2021	BenchmarkingClassification	CodeCode Available	1	5
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts	May 24, 2022	Few-Shot LearningLanguage Modelling	CodeCode Available	1	5
Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences	Sep 24, 2020	Data AugmentationDomain Adaptation	CodeCode Available	1	5
AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks	Jan 23, 2022	DecoderHandwriting Recognition	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