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 3401–3425 of 10307 papers

TitleStatusHype
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space—0
Automatic Graphic Logo Detection via Fast Region-based Convolutional Networks—0
Deepfake Detection of Face Images based on a Convolutional Neural Network—0
Deepfake Audio Detection Using Spectrogram-based Feature and Ensemble of Deep Learning Models—0
Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer—0
An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products—0
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue—0
Efficient Transfer Learning in Diffusion Models via Adversarial Noise—0
Efficient Transfer Learning Schemes for Personalized Language Modeling using Recurrent Neural Network—0
Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weight—0
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification—0
Evaluation of Transfer Learning for Polish with a Text-to-Text Model—0
EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition—0
An Unified Search and Recommendation Foundation Model for Cold-Start Scenario—0
ET-GAN: Cross-Language Emotion Transfer Based on Cycle-Consistent Generative Adversarial Networks—0
Causal Time-Series Synchronization for Multi-Dimensional Forecasting—0
Causal Transfer for Imitation Learning and Decision Making under Sensor-shift—0
Actionable Phrase Detection using NLP—0
Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms—0
ELCC: the Emergent Language Corpus Collection—0
Cause-Effect Preservation and Classification using Neurochaos Learning—0
Electron-nucleus cross sections from transfer learning—0
DeepEthnic: Multi-Label Ethnic Classification from Face Images—0
A multitask transfer learning framework for the prediction of virus-human protein-protein interactions—0
Deep Ensembling for Perceptual Image Quality Assessment—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