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 5776–5800 of 10307 papers

TitleStatusHype
Mask Usage Recognition using Vision Transformer with Transfer Learning and Data Augmentation—0
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis—0
Deep Learning based Intelligent Coin-tap Test for Defect RecognitionCode0
simCrossTrans: A Simple Cross-Modality Transfer Learning for Object Detection with ConvNets or Vision TransformersCode0
A Study on Robustness to Perturbations for Representations of Environmental Sound—0
Towards 3D Scene Understanding by Referring Synthetic Models—0
Transferable Class-Modelling for Decentralized Source Attribution of GAN-Generated ImagesCode0
A Closer Look at Knowledge Distillation with Features, Logits, and Gradients—0
AdaVocoder: Adaptive Vocoder for Custom Voice—0
Multi-Modal Masked Pre-Training for Monocular Panoramic Depth CompletionCode0
Analysis and Adaptation of YOLOv4 for Object Detection in Aerial Images—0
Performance of Deep Learning models with transfer learning for multiple-step-ahead forecasts in monthly time series—0
Feature-informed Latent Space Regularization for Music Source Separation—0
POSTER: Diagnosis of COVID-19 through Transfer Learning Techniques on CT Scans: A Comparison of Deep Learning Models—0
Semantic-diversity transfer network for generalized zero-shot learning via inner disagreement based OOD detector—0
Image Super-Resolution With Deep Variational Autoencoders—0
Triangular Transfer: Freezing the Pivot for Triangular Machine Translation—0
Transfer learning for cross-modal demand prediction of bike-share and public transit—0
Transforming Sequence Tagging Into A Seq2Seq Task—0
CtlGAN: Few-shot Artistic Portraits Generation with Contrastive Transfer Learning—0
Object discovery and representation networksCode0
Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-TuningCode0
Bures Joint Distribution Alignment with Dynamic Margin for Unsupervised Domain Adaptation—0
Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-modal Knowledge Transfer—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—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