SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7901–7925 of 10307 papers

TitleStatusHype
A lightweight and accurate YOLO-like network for small target detection in Aerial Imagery—0
Multimodal Knowledge Learning for Named Entity Disambiguation—0
Spectro-Temporal RF Identification using Deep Learning—0
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence—0
AlgoRxplorers | Precision in Mutation: Enhancing Drug Design with Advanced Protein Stability Prediction Tools—0
Multimodal Quantitative Language for Generative Recommendation—0
Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios—0
Multimodal Sentiment Analysis with Missing Modality: A Knowledge-Transfer Approach—0
AlexU-BackTranslation-TL at SemEval-2020 Task 12: Improving Offensive Language Detection Using Data Augmentation and Transfer Learning—0
Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation—0
Multi-modal Transfer Learning between Biological Foundation Models—0
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels—0
Multi-modal wound classification using wound image and location by Xception and Gaussian Mixture Recurrent Neural Network (GMRNN)—0
Multi-Module Recurrent Neural Networks with Transfer Learning—0
A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems—0
Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustness—0
Multi-objective Neural Architecture Search with Almost No Training—0
Speech-Based Depression Prediction Using Encoder-Weight-Only Transfer Learning and a Large Corpus—0
MultIOD: Rehearsal-free Multihead Incremental Object Detector—0
Multi-Organ Cancer Classification and Survival Analysis—0
Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation—0
Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network—0
Multi-path Neural Networks for On-device Multi-domain Visual Classification—0
Multiphase flow prediction with deep neural networks—0
Multi-Platform Methane Plume Detection via Model and Domain Adaptation—0
Show:102550
← PrevPage 317 of 413Next →
All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified