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

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Showing 2501–2525 of 10307 papers

TitleStatusHype
Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images—0
Deep Transfer Learning: Model Framework and Error Analysis—0
Best of Both Worlds: Robust Accented Speech Recognition with Adversarial Transfer Learning—0
Best Arm Identification under Additive Transfer Bandits—0
BeST -- A Novel Source Selection Metric for Transfer Learning—0
An empirical investigation into audio pipeline approaches for classifying bird species—0
A Deep Learning and Knowledge Transfer Based Architecture for Social Media User Characteristic Determination—0
A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications—0
Deep Transfer Learning on Satellite Imagery Improves Air Quality Estimates in Developing Nations—0
BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweets—0
BERT-PersNER: A New Model for Persian Named Entity Recognition—0
An Empirical Evaluation of Text Representation Schemes on Multilingual Social Web to Filter the Textual Aggression—0
A Deep Generative Framework for Joint Households and Individuals Population Synthesis—0
An Empirical Analysis on the Vulnerabilities of End-to-End Speech Segregation Models—0
Deep Transfer Learning for Thermal Dynamics Modeling in Smart Buildings—0
Deep Transfer Learning For Whole-Brain fMRI Analyses—0
BERT Fine-Tuning for Sentiment Analysis on Indonesian Mobile Apps Reviews—0
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions—0
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning—0
A Deeper Look at 3D Shape Classifiers—0
A Bayesian Hierarchical Model for Generating Synthetic Unbalanced Power Distribution Grids—0
Deep Transfer Learning for WiFi Localization—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—0
An embedding for EEG signals learned using a triplet loss—0
Benchmarks and models for entity-oriented polarity detection—0
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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