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 4951–5000 of 10307 papers

TitleStatusHype
SHiFT: An Efficient, Flexible Search Engine for Transfer LearningCode0
Towards Deep Industrial Transfer Learning: Clustering for Transfer Case Selection—0
In Rain or Shine: Understanding and Overcoming Dataset Bias for Improving Robustness Against Weather Corruptions for Autonomous Vehicles—0
Deep Speech Based End-to-End Automated Speech Recognition (ASR) for Indian-English Accents—0
Knowledge distillation with error-correcting transfer learning for wind power prediction—0
Efficient Argument Structure Extraction with Transfer Learning and Active Learning—0
Proper Reuse of Image Classification Features Improves Object Detection—0
A Unified Framework for Domain Adaptive Pose EstimationCode1
Diverse Preference Augmentation with Multiple Domains for Cold-start RecommendationsCode0
Autonomous crater detection on asteroids using a fully-convolutional neural network—0
Unified and Effective Ensemble Knowledge Distillation—0
Scaling Language Model Size in Cross-Device Federated Learning—0
Maze Learning using a Hyperdimensional Predictive Processing Cognitive Architecture—0
Real-Time and Robust 3D Object Detection Within Road-Side LiDARs Using Domain Adaptation—0
Leverage Your Local and Global Representations: A New Self-Supervised Learning StrategyCode1
Domain Adaptation for Sparse-Data Settings: What Do We Gain by Not Using Bert?—0
A Temporal Learning Approach to Inpainting Endoscopic Specularities and Its effect on Image Correspondence—0
Traffic4cast at NeurIPS 2021 -- Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial ProcessesCode1
A fuzzy distance-based ensemble of deep models for cervical cancer detectionCode1
CycDA: Unsupervised Cycle Domain Adaptation from Image to VideoCode0
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer DatasetCode1
Transfer Learning Framework for Low-Resource Text-to-Speech using a Large-Scale Unlabeled Speech Corpus—0
Parameter-efficient Model Adaptation for Vision TransformersCode1
Kernel Modulation: A Parameter-Efficient Method for Training Convolutional Neural Networks—0
Enabling hand gesture customization on wrist-worn devices—0
Learning to Prompt for Open-Vocabulary Object Detection with Vision-Language ModelCode1
A Framework of Meta Functional Learning for Regularising Knowledge Transfer—0
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations—0
Using Domain Knowledge for Low Resource Named Entity Recognition—0
Mugs: A Multi-Granular Self-Supervised Learning FrameworkCode1
Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison—0
Benchmarking Algorithms for Automatic License Plate Recognition—0
GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI DetectionCode1
Medicinal Boxes Recognition on a Deep Transfer Learning Augmented Reality Mobile Application—0
Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data—0
A Comparative Evaluation Of Transformer Models For De-Identification Of Clinical Text Data—0
Facial Action Unit Recognition Based on Transfer Learning—0
Model LEGO: Creating Models Like Disassembling and Assembling Building BlocksCode1
Semi-supervised machine learning model for analysis of nanowire morphologies from transmission electron microscopy imagesCode0
Interpretation of Chest x-rays affected by bullets using deep transfer learning—0
Digital Fingerprinting of Microstructures—0
Learning Losses for Strategic Classification—0
DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation LearningCode1
Cross-Domain Few-Shot Semantic SegmentationCode1
Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?Code0
Pastiche Master: Exemplar-Based High-Resolution Portrait Style TransferCode3
A Two-Stage Federated Transfer Learning Framework in Medical Images Classification on Limited Data: A COVID-19 Case Study—0
Efficient Few-Shot Object Detection via Knowledge InheritanceCode1
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis—0
Feature Distribution Matching for Federated Domain GeneralizationCode0
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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