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 3951–4000 of 10307 papers

TitleStatusHype
Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning—0
Spatio-Temporal Crop Aggregation for Video Representation Learning—0
Progressive Knowledge Transfer Based on Human Visual Perception Mechanism for Perceptual Quality Assessment of Point Clouds—0
On the Design of Communication-Efficient Federated Learning for Health Monitoring—0
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data FormatCode1
Cross-project Defect Prediction with An Enhanced Transfer Boosting AlgorithmCode0
Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike TrainsCode1
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime—0
Data-efficient Modeling of Optical Matrix Multipliers Using Transfer Learning—0
Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST)—0
Transferability Estimation Based On Principal Gradient Expectation—0
Lifelong Embedding Learning and Transfer for Growing Knowledge GraphsCode1
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generationCode0
Reinforced Genetic Algorithm for Structure-based Drug DesignCode1
Hypernetworks for Zero-shot Transfer in Reinforcement Learning—0
Higher-order Knowledge Transfer for Dynamic Community Detection with Great Changes—0
Inapplicable Actions Learning for Knowledge Transfer in Reinforcement Learning—0
Learning to Learn: How to Continuously Teach Humans and Machines—0
Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis—0
Automated Detection of Dolphin Whistles with Convolutional Networks and Transfer Learning—0
Combined Peak Reduction and Self-Consumption Using Proximal Policy Optimization—0
MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding—0
Estimation and inference for transfer learning with high-dimensional quantile regression—0
An Automatic SOAP Classification System Using Weakly Supervision And Transfer Learning—0
Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning—0
Transfer RL via the Undo Maps Formalism—0
Multi-fidelity Gaussian Process for Biomanufacturing Process Modeling with Small Data—0
MCFFA-Net: Multi-Contextual Feature Fusion and Attention Guided Network for Apple Foliar Disease Classification—0
XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation LearningCode1
Unsupervised Continual Semantic Adaptation through Neural RenderingCode1
Differentially Private Image Classification from FeaturesCode0
DeepTaster: Adversarial Perturbation-Based Fingerprinting to Identify Proprietary Dataset Use in Deep Neural Networks—0
Cross-domain Transfer of defect features in technical domains based on partial target data—0
PAC-Bayes Compression Bounds So Tight That They Can Explain GeneralizationCode1
On the impact of incorporating task-information in learning-based image denoising—0
Enhancing team performance with transfer-learning during real-world human-robot collaboration—0
Semi-Supervised Lifelong Language Learning—0
Continual Learning of Natural Language Processing Tasks: A Survey—0
Agent-Specific Deontic Modality Detection in Legal Language—0
A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks—0
Compiler Provenance Recovery for Multi-CPU Architectures Using a Centrifuge Mechanism—0
Boosting Personalised Musculoskeletal Modelling with Physics-informed Knowledge Transfer—0
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning—0
Transfer Learning for Contextual Multi-armed Bandits—0
Classification of Human Monkeypox Disease Using Deep Learning Models and Attention Mechanisms—0
Classification of Melanocytic Nevus Images using BigTransfer (BiT)—0
Multi-Spectral Image Classification with Ultra-Lean Complex-Valued Models—0
Can You Label Less by Using Out-of-Domain Data? Active & Transfer Learning with Few-shot Instructions—0
Understanding and Improving Visual Prompting: A Label-Mapping PerspectiveCode1
Orientation recognition and correction of Cardiac MRI with deep neural networkCode0
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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