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 7451–7500 of 10307 papers

TitleStatusHype
Force myography benchmark data for hand gesture recognition and transfer learningCode0
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization—0
Group Knowledge Transfer: Federated Learning of Large CNNs at the EdgeCode1
Pan-Cancer Computational Histopathology (PC-CHiP) analysis using deep learningCode1
Solving Linear Inverse Problems Using the Prior Implicit in a DenoiserCode1
Evaluation of Federated Learning in Phishing Email Detection—0
Few-shot Knowledge Transfer for Fine-grained Cartoon Face GenerationCode2
Practical and sample efficient zero-shot HPO—0
An Uncertainty-aware Transfer Learning-based Framework for Covid-19 DiagnosisCode1
Reed at SemEval-2020 Task 9: Fine-Tuning and Bag-of-Words Approaches to Code-Mixed Sentiment Analysis—0
Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence—0
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural NetworksCode1
Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning—0
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings—0
Enhanced Transfer Learning for Autonomous Driving with Systematic Accident Simulation—0
Multi-task learning for natural language processing in the 2020s: where are we going?—0
Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models—0
Rethinking CNN Models for Audio ClassificationCode1
Dog Identification using Soft Biometrics and Neural Networks—0
Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student LearningCode0
Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning—0
TinyTL: Reduce Activations, Not Trainable Parameters for Efficient On-Device LearningCode2
A Transfer Learning End-to-End ArabicText-To-Speech (TTS) Deep Architecture—0
PointContrast: Unsupervised Pre-training for 3D Point Cloud UnderstandingCode1
NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture SearchCode1
Generative Hierarchical Features from Synthesizing ImagesCode1
XMixup: Efficient Transfer Learning with Auxiliary Samples by Cross-domain Mixup—0
Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot LearningCode1
AquaVision: Automating the detection of waste in water bodies using deep transfer learningCode1
Classification of Diabetic Retinopathy via Fundus Photography: Utilization of Deep Learning Approaches to Speed up Disease Detection—0
Structure Mapping for Transferability of Causal ModelsCode0
DWMD: Dimensional Weighted Orderwise Moment Discrepancy for Domain-specific Hidden Representation Matching—0
Semi-Supervised Learning Approach to Discover Enterprise User Insights from Feedback and Support—0
ImageNet performance correlates with pose estimation robustness and generalization on out-of-domain data—0
Domain2Vec: Domain Embedding for Unsupervised Domain AdaptationCode0
Multi-Stage Influence Function—0
CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis—0
2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge—0
Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources—0
Vehicle Detection of Multi-source Remote Sensing Data Using Active Fine-tuning Network—0
Unsupervised machine learning via transfer learning and k-means clustering to classify materials image dataCode1
Transfer Deep Reinforcement Learning-enabled Energy Management Strategy for Hybrid Tracked Vehicle—0
Advances in Deep Learning for Hyperspectral Image Analysis--Addressing Challenges Arising in Practical Imaging Scenarios—0
Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs—0
On Robustness and Transferability of Convolutional Neural NetworksCode1
Do Adversarially Robust ImageNet Models Transfer Better?Code1
Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning—0
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows—0
Boosting Weakly Supervised Object Detection with Progressive Knowledge TransferCode1
Visualizing Transfer Learning—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