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 6601–6625 of 10307 papers

TitleStatusHype
ROD: Reception-aware Online Distillation for Sparse GraphsCode0
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica—0
Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things ApplicationCode0
An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products—0
Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings—0
Developing efficient transfer learning strategies for robust scene recognition in mobile robotics using pre-trained convolutional neural networks—0
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks—0
Detail Preserving Residual Feature Pyramid Modules for Optical Flow—0
Size doesn't matter: predicting physico- or biochemical properties based on dozens of molecules—0
Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sørensen-Dice Coefficient Loss and Transfer Learning—0
Self-transfer learning via patches: A prostate cancer triage approach based on bi-parametric MRI—0
Time-Frequency Analysis based Deep Interference Classification for Frequency Hopping System—0
Window Detection In Facade Imagery: A Deep Learning Approach Using Mask R-CNN—0
Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production—0
Molecular Subtype Prediction for Breast Cancer Using H&E Specialized Backbone—0
Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System—0
Similarity metrics for Different Market Scenarios in Abides—0
Improved Reinforcement Learning in Cooperative Multi-agent Environments Using Knowledge Transfer—0
Class dependency based learning using Bi-LSTM coupled with the transfer learning of VGG16 for the diagnosis of Tuberculosis from chest x-rays—0
Confidence Aware Neural Networks for Skin Cancer Detection—0
Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation functionCode0
Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the WildCode0
Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction—0
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data—0
Online Learning for Recommendations at Grubhub—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