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 4126–4150 of 10307 papers

TitleStatusHype
Data Quality Monitoring through Transfer Learning on Anomaly Detection for the Hadron Calorimeters—0
A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning—0
Data Optimisation for a Deep Learning Recommender System—0
Automated detection of oral pre-cancerous tongue lesions using deep learning for early diagnosis of oral cavity cancer—0
Data InStance Prior (DISP) in Generative Adversarial Networks—0
Data Instance Prior for Transfer Learning in GANs—0
Automated detection of gibbon calls from passive acoustic monitoring data using convolutional neural networks in the "torch for R" ecosystem—0
Data Generation Using Pass-phrase-dependent Deep Auto-encoders for Text-Dependent Speaker Verification—0
Data Fusion of Deep Learned Molecular Embeddings for Property Prediction—0
Automated Detection of Dolphin Whistles with Convolutional Networks and Transfer Learning—0
Geometric Framework for Cell Oversegmentation—0
Geometry-Aware Network for Domain Adaptive Semantic Segmentation—0
Data-Free Knowledge Transfer: A Survey—0
Automated Detection of Coronary Artery Stenosis in X-ray Angiography using Deep Neural Networks—0
Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory—0
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation—0
Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement—0
Amplitude-Independent Machine Learning for PPG through Visibility Graphs and Transfer Learning—0
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks—0
Adaptive Trajectory Prediction via Transferable GNN—0
Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies—0
Data-efficient Modeling of Optical Matrix Multipliers Using Transfer Learning—0
Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine Translation.—0
Data-Efficient Methods for Dialogue Systems—0
Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection—0
Show:102550
← PrevPage 166 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