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
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels—0
Unveiling the Potential of Deep Learning Models for Solar Flare Prediction in Near-Limb Regions—0
SINCERE: Supervised Information Noise-Contrastive Estimation REvisitedCode0
Incorporating Ensemble and Transfer Learning For An End-To-End Auto-Colorized Image Detection Model—0
Physics-Informed Solution of The Stationary Fokker-Plank Equation for a Class of Nonlinear Dynamical Systems: An Evaluation Study—0
Comparative Evaluation of Transfer Learning for Classification of Brain Tumor Using MRI—0
Cross-modal Alignment with Optimal Transport for CTC-based ASR—0
Crack-Net: Prediction of Crack Propagation in Composites—0
Robust Navigation with Cross-Modal Fusion and Knowledge TransferCode0
EMGTFNet: Fuzzy Vision Transformer to decode Upperlimb sEMG signals for Hand Gestures Recognition—0
A Deep Learning Sequential Decoder for Transient High-Density Electromyography in Hand Gesture Recognition Using Subject-Embedded Transfer Learning—0
Randomize to Generalize: Domain Randomization for Runway FOD Detection—0
Attention Is All You Need For Blind Room Volume Estimation—0
Multiply Robust Federated Estimation of Targeted Average Treatment Effects—0
Unsupervised Representations Improve Supervised Learning in Speech Emotion Recognition—0
Understanding Calibration of Deep Neural Networks for Medical Image Classification—0
STemGAN: spatio-temporal generative adversarial network for video anomaly detection—0
Domain Adaptation for Arabic Machine Translation: The Case of Financial Texts—0
Reduce, Reuse, Recycle: Is Perturbed Data better than Other Language augmentation for Low Resource Self-Supervised Speech Models—0
Identification of pneumonia on chest x-ray images through machine learning—0
Brain Tumor Detection Using Deep Learning Approaches—0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild—0
Hand Gesture Recognition with Two Stage Approach Using Transfer Learning and Deep Ensemble Learning—0
Dense 2D-3D Indoor Prediction with Sound via Aligned Cross-Modal DistillationCode0
Using Artificial Intelligence for the Automation of Knitting Patterns—0
Leveraging Speech PTM, Text LLM, and Emotional TTS for Speech Emotion Recognition—0
Semi-supervised Domain Adaptation in Graph Transfer Learning—0
Toward efficient resource utilization at edge nodes in federated learning—0
Cross-modal and Cross-domain Knowledge Transfer for Label-free 3D Segmentation—0
A Hierarchical Neural Framework for Classification and its Explanation in Large Unstructured Legal Documents—0
PDRL: Multi-Agent based Reinforcement Learning for Predictive Monitoring—0
CLIP-based Synergistic Knowledge Transfer for Text-based Person RetrievalCode0
Solving Neural Field Equations using Physics Informed Neural NetworksCode0
Learning Unified Distance Metric Across Diverse Data Distributions with Parameter-Efficient Transfer Learning—0
An Unified Search and Recommendation Foundation Model for Cold-Start Scenario—0
One-stage Modality Distillation for Incomplete Multimodal Learning—0
Improved Breast Cancer Diagnosis through Transfer Learning on Hematoxylin and Eosin Stained Histology Images—0
MIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic Systems—0
Semantic Parsing in Limited Resource Conditions—0
Enhancing Performance, Calibration Time and Efficiency in Brain-Machine Interfaces through Transfer Learning and Wearable EEG Technology—0
Efficiently Robustify Pre-trained Models—0
Adaptive Prompt Learning with Distilled Connective Knowledge for Implicit Discourse Relation RecognitionCode0
Safe and Accelerated Deep Reinforcement Learning-based O-RAN Slicing: A Hybrid Transfer Learning ApproachCode0
Learning from Auxiliary Sources in Argumentative Revision Classification—0
TransNet: A Transfer Learning-Based Network for Human Action Recognition—0
Continual Learning with Dirichlet Generative-based Rehearsal—0
Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table TransformersCode0
Dynamic Visual Prompt Tuning for Parameter Efficient Transfer Learning—0
Distributionally Robust Transfer Learning—0
A 3M-Hybrid Model for the Restoration of Unique Giant Murals: A Case Study on the Murals of Yongle Palace—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