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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1551–1600 of 10307 papers

TitleStatusHype
A Situated Dialogue System for Learning Structural Concepts in Blocks World—0
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification—0
A Simple yet Effective Joint Training Method for Cross-Lingual Universal Dependency Parsing—0
A General Multiple Data Augmentation Based Framework for Training Deep Neural Networks—0
An Explainable Vision Transformer with Transfer Learning Combined with Support Vector Machine Based Efficient Drought Stress Identification—0
Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces—0
A general method for regularizing tensor decomposition methods via pseudo-data—0
A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks—0
Adapt and Align to Improve Zero-Shot Sketch-Based Image Retrieval—0
A General Class of Transfer Learning Regression without Implementation Cost—0
ACES -- Automatic Configuration of Energy Harvesting Sensors with Reinforcement Learning—0
Adaptable image quality assessment using meta-reinforcement learning of task amenability—0
Combining General and Personalized Models for Epilepsy Detection with Hyperdimensional Computing—0
Combining human parsing with analytical feature extraction and ranking schemes for high-generalization person reidentification—0
A General Approach to Domain Adaptation with Applications in Astronomy—0
A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition—0
A general approach to bridge the reality-gap—0
Adaptable Automation with Modular Deep Reinforcement Learning and Policy Transfer—0
2M-NER: Contrastive Learning for Multilingual and Multimodal NER with Language and Modal Fusion—0
A serial dual-channel library occupancy detection system based on Faster RCNN—0
A Sequential Self Teaching Approach for Improving Generalization in Sound Event Recognition—0
Age and Gender Prediction using Deep CNNs and Transfer Learning—0
AGE2HIE: Transfer Learning from Brain Age to Predicting Neurocognitive Outcome for Infant Brain Injury—0
A Sequence Matching Network for Polyphonic Sound Event Localization and Detection—0
AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization—0
A Centralized-Distributed Transfer Model for Cross-Domain Recommendation Based on Multi-Source Heterogeneous Transfer Learning—0
Combining Federated Learning and Control: A Survey—0
Combining Image Features and Patient Metadata to Enhance Transfer Learning—0
CommonCanvas: Open Diffusion Models Trained on Creative-Commons Images—0
Monocular Cyclist Detection with Convolutional Neural Networks—0
A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding—0
Combined Scaling for Zero-shot Transfer Learning—0
A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning—0
A Semiparametric Efficient Approach To Label Shift Estimation and Quantification—0
A Game-Theoretic Perspective of Generalization in Reinforcement Learning—0
Combinets: Creativity via Recombination of Neural Networks—0
A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification—0
A Self-attention Knowledge Domain Adaptation Network for Commercial Lithium-ion Batteries State-of-health Estimation under Shallow Cycles—0
Against Multifaceted Graph Heterogeneity via Asymmetric Federated Prompt Learning—0
A Segmentation Foundation Model for Diverse-type Tumors—0
A Seed-Augment-Train Framework for Universal Digit Classification—0
Adam Mickiewicz University’s English-Hausa Submissions to the WMT 2021 News Translation Task—0
Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population—0
Combining Behaviors with the Successor Features Keyboard—0
A scoping review of transfer learning research on medical image analysis using ImageNet—0
Boosting-GNN: Boosting Algorithm for Graph Networks on Imbalanced Node Classification—0
A Scenario-Based Functional Testing Approach to Improving DNN Performance—0
A Scaling Law for Syn-to-Real Transfer: How Much Is Your Pre-training Effective?—0
Accurate Prostate Cancer Detection and Segmentation on Biparametric MRI using Non-local Mask R-CNN with Histopathological Ground Truth—0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos—0
Show:102550
← PrevPage 32 of 207Next →
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