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 4851–4900 of 10307 papers

TitleStatusHype
Patch-GAN Transfer Learning with Reconstructive Models for Cloud Removal—0
Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models—0
Patent-publication pairs for the detection of knowledge transfer from research to industry: reducing ambiguities with word embeddings and references—0
Path Planning of Cleaning Robot with Reinforcement Learning—0
Pathway to a fully data-driven geotechnics: lessons from materials informatics—0
Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer—0
Patient-Specific Finetuning of Deep Learning Models for Adaptive Radiotherapy in Prostate CT—0
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching—0
PaXNet: Dental Caries Detection in Panoramic X-ray using Ensemble Transfer Learning and Capsule Classifier—0
Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning—0
Pay Attention to Features, Transfer Learn Faster CNNs—0
PBNR: Prompt-based News Recommender System—0
PCA-Initialized Deep Neural Networks Applied To Document Image Analysis—0
PCAPVision: PCAP-Based High-Velocity and Large-Volume Network Failure Detection—0
PCNN: Environment Adaptive Model Without Finetuning—0
PCONet: A Convolutional Neural Network Architecture to Detect Polycystic Ovary Syndrome (PCOS) from Ovarian Ultrasound Images—0
PDALN: Progressive Domain Adaptation over a Pre-trained Model for Low-Resource Cross-Domain Named Entity Recognition—0
PDRL: Multi-Agent based Reinforcement Learning for Predictive Monitoring—0
Peak-Controlled Logits Poisoning Attack in Federated Distillation—0
Peer is Your Pillar: A Data-unbalanced Conditional GANs for Few-shot Image Generation—0
PEMNET: A Transfer Learning-based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems—0
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction—0
PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning—0
Percept, Chat, and then Adapt: Multimodal Knowledge Transfer of Foundation Models for Open-World Video Recognition—0
Performance Embeddings: A Similarity-based Approach to Automatic Performance Optimization—0
Performance Estimation of Synthesis Flows cross Technologies using LSTMs and Transfer Learning—0
Performance Evaluation of Convolutional Neural Networks for Gait Recognition—0
Performance Evaluation of Image Enhancement Techniques on Transfer Learning for Touchless Fingerprint Recognition—0
Performance Evaluation of Sentiment Analysis on Text and Emoji Data Using End-to-End, Transfer Learning, Distributed and Explainable AI Models—0
Performance of Deep Learning models with transfer learning for multiple-step-ahead forecasts in monthly time series—0
Performance of Transfer Learning Model vs. Traditional Neural Network in Low System Resource Environment—0
Per-pixel Classification Rebar Exposures in Bridge Eye-inspection—0
PersianMind: A Cross-Lingual Persian-English Large Language Model—0
Persian Natural Language Inference: A Meta-learning approach—0
Persian Semantic Role Labeling Using Transfer Learning and BERT-Based Models—0
Personalization of Wearable Sensor-Based Joint Kinematic Estimation Using Computer Vision for Hip Exoskeleton Applications—0
Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization—0
Personalized Continual EEG Decoding: Retaining and Transferring Knowledge—0
Personalized Dynamics Models for Adaptive Assistive Navigation Systems—0
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer—0
Personalized Federated Learning via Backbone Self-Distillation—0
Personalized Federated Learning with Adaptive Feature Aggregation and Knowledge Transfer—0
Personalized Human Activity Recognition Using Convolutional Neural Networks—0
Personalized Patent Claim Generation and Measurement—0
Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts—0
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes—0
Personalized Semi-Supervised Federated Learning for Human Activity Recognition—0
Personalized Subgraph Federated Learning with Differentiable Auxiliary Projections—0
Personalizing a Dialogue System with Transfer Reinforcement Learning—0
Personalizing Smartwatch Based Activity Recognition Using 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