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 7001–7050 of 10307 papers

TitleStatusHype
Liver Fibrosis and NAS scoring from CT images using self-supervised learning and texture encodingCode0
NemaNet: A convolutional neural network model for identification of nematodes soybean crop in brazil—0
Moving from Cross-Project Defect Prediction to Heterogeneous Defect Prediction: A Partial Replication Study—0
Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection—0
Transfer Learning-Based Model Protection With Secret Key—0
Transfer Learning based Speech Affect Recognition in Urdu—0
Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning—0
Transfer learning from High-Resource to Low-Resource Language Improves Speech Affect Recognition Classification Accuracy—0
A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models—0
Deep Neural Network Models Compression—0
End-to-end acoustic modelling for phone recognition of young readers—0
Contrastive Learning Meets Transfer Learning: A Case Study In Medical Image Analysis—0
Automated Detection of Coronary Artery Stenosis in X-ray Angiography using Deep Neural Networks—0
Learning Invariant Representations across Domains and Tasks—0
Domain Generalization: A Survey—0
The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural NetworkCode0
Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths—0
AdeNet: Deep learning architecture that identifies damaged electrical insulators in power linesCode0
CG-CNN: Self-Supervised Feature Extraction Through Contextual Guidance and Transfer Learning—0
Fast Adaptation with Linearized Neural Networks—0
TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning—0
Understanding WiFi Signal Frequency Features for Position-Independent Gesture Sensing—0
The Relevance of the Source Language in Transfer Learning for ASR—0
A Machine Learning Approach for Predicting Human Preference for Graph Layouts—0
Embedded Knowledge Distillation in Depth-Level Dynamic Neural Network—0
Deep Bag-of-Sub-Emotions for Depression Detection in Social Media—0
Improved Automated Machine Learning from Transfer LearningCode0
Scalable Causal Domain AdaptationCode0
ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose EstimationCode0
Neural Code SummarizationCode0
Multi-task transfer learning for finding actionable information from crisis-related messages on social media—0
Three-dimensional Coherent X-ray Diffraction Imaging via Deep Convolutional Neural Networks—0
Scalable Multiagent Driving Policies For Reducing Traffic CongestionCode0
PharmKE: Knowledge Extraction Platform for Pharmaceutical Texts using Transfer Learning—0
Application of Transfer Learning to Sign Language Recognition using an Inflated 3D Deep Convolutional Neural NetworkCode0
Hyperparameter Transfer Learning with Adaptive Complexity—0
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning—0
Web Table Classification based on Visual Features—0
"Train one, Classify one, Teach one" -- Cross-surgery transfer learning for surgical step recognition—0
Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants—0
Transfer Learning with Convolutional Neural Networks for Rainfall Detection in Single ImagesCode0
Generalized and Transferable Patient Language Representation for Phenotyping with Limited Data—0
Classification of Breast Cancer Lesions in Ultrasound Images by using Attention Layer and loss Ensembles in Deep Convolutional Neural Networks—0
Comparative evaluation of CNN architectures for Image Caption GenerationCode0
A Novel Deep Learning Method for Textual Sentiment Analysis—0
A microservice-based framework for exploring data selection in cross-building knowledge transfer—0
RUBERT: A Bilingual Roman Urdu BERT Using Cross Lingual Transfer Learning—0
Bilingual Language Modeling, A transfer learning technique for Roman Urdu—0
ReINTEL Challenge 2020: Exploiting Transfer Learning Models for Reliable Intelligence Identification on Vietnamese Social Network Sites—0
Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution—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