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 7401–7450 of 10307 papers

TitleStatusHype
Large-scale Transfer Learning for Low-resource Spoken Language Understanding—0
Enhancing Speech Intelligibility in Text-To-Speech Synthesis using Speaking Style ConversionCode1
Adversarial Knowledge Transfer from Unlabeled DataCode0
Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task—0
Facial Expression Recognition Under Partial Occlusion from Virtual Reality Headsets based on Transfer LearningCode0
An Efficient Confidence Measure-Based Evaluation Metric for Breast Cancer Screening Using Bayesian Neural NetworksCode0
Transfer Learning Approaches for Streaming End-to-End Speech Recognition System—0
Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer—0
Efficient Integration of Multi-channel Information for Speaker-independent Speech Separation—0
Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey—0
Transfer Learning for Protein Structure Classification at Low ResolutionCode0
Unsupervised Feature Learning by Cross-Level Instance-Group DiscriminationCode1
One for Many: Transfer Learning for Building HVAC Control—0
Audio Spoofing Verification using Deep Convolutional Neural Networks by Transfer LearningCode1
Exploring the parameter reusability of CNN—0
Using UNet and PSPNet to explore the reusability principle of CNN parameters—0
Hybrid Template Canonical Correlation Analysis Method for Enhancing SSVEP Recognition under data-limited Condition—0
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval—0
aschern at SemEval-2020 Task 11: It Takes Three to Tango: RoBERTa, CRF, and Transfer LearningCode1
Federated Transfer Learning with Dynamic Gradient Aggregation—0
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation—0
MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray ScansCode1
Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies—0
A Novel Method For Designing Transferable Soft Sensors And Its Application—0
Duality Diagram Similarity: a generic framework for initialization selection in task transfer learningCode1
Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs—0
Prompt Agnostic Essay Scorer: A Domain Generalization Approach to Cross-prompt Automated Essay ScoringCode0
An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch—0
Memory Efficient Class-Incremental Learning for Image Classification—0
Online Few-shot Gesture Learning on a Neuromorphic Processor—0
Shape Adaptor: A Learnable Resizing ModuleCode1
A Foliated View of Transfer Learning—0
Discriminative Partial Domain Adversarial Network—0
Principal Feature Visualisation in Convolutional Neural NetworksCode1
FTL: A universal framework for training low-bit DNNs via Feature Transfer—0
n-Reference Transfer Learning for Saliency PredictionCode1
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation—0
Deep Transferring QuantizationCode1
An Explainable Machine Learning Model for Early Detection of Parkinson's Disease using LIME on DaTscan Imagery—0
Self-supervised Visual Attribute Learning for Fashion Compatibility—0
Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware—0
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge—0
An Improvement for Capsule Networks using Depthwise Separable Convolution—0
Beyond H-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence—0
Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak—0
COVID-19 therapy target discovery with context-aware literature mining—0
Bilevel Continual LearningCode1
Learning Representations for Axis-Aligned Decision Forests through Input Perturbation—0
Modular Transfer Learning with Transition Mismatch Compensation for Excessive Disturbance Rejection—0
Show:102550
← PrevPage 149 of 207Next →
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