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 2551–2600 of 10307 papers

TitleStatusHype
Force myography benchmark data for hand gesture recognition and transfer learningCode0
CSTRL: Context-Driven Sequential Transfer Learning for Abstractive Radiology Report SummarizationCode0
HOLMES: HOLonym-MEronym based Semantic inspection for Convolutional Image ClassifiersCode0
Homogeneous Online Transfer Learning with Online Distribution Discrepancy MinimizationCode0
Fleet Control using Coregionalized Gaussian Process Policy IterationCode0
How does Multi-Task Training Affect Transformer In-Context Capabilities? Investigations with Function ClassesCode0
Flat Posterior Does Matter For Bayesian Model AveragingCode0
How good are variational autoencoders at transfer learning?Code0
Flexible Option LearningCode0
FissionFusion: Fast Geometric Generation and Hierarchical Souping for Medical Image AnalysisCode0
3D-PointZshotS: Geometry-Aware 3D Point Cloud Zero-Shot Semantic Segmentation Narrowing the Visual-Semantic GapCode0
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer LearningCode0
Finger Pose Estimation for Under-screen Fingerprint SensorCode0
Cross-View Policy Learning for Street NavigationCode0
Adaptive Meta-Domain Transfer Learning (AMDTL): A Novel Approach for Knowledge Transfer in AICode0
Decoupled Self Attention for Accurate One Stage Object DetectionCode0
A Tulu Resource for Machine TranslationCode0
Fine-grained Sentiment Classification using BERTCode0
First-frame Supervised Video Polyp Segmentation via Propagative and Semantic Dual-teacher NetworkCode0
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited tripletsCode0
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant SetupCode0
Hyperparameters in Score-Based Membership Inference AttacksCode0
A Generative Framework for Low-Cost Result Validation of Machine Learning-as-a-Service InferenceCode0
Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning TechniquesCode0
Few-shot learning for COVID-19 Chest X-Ray Classification with Imbalanced Data: An Inter vs. Intra Domain StudyCode0
Few-Shot Learning for Image Classification of Common FloraCode0
Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer LearningCode0
Cross-project Defect Prediction with An Enhanced Transfer Boosting AlgorithmCode0
Few-Shot Fruit Segmentation via Transfer LearningCode0
Deep Categorization with Semi-Supervised Self-Organizing MapsCode0
Few-shot calibration of low-cost air pollution (PM2.5) sensors using meta-learningCode0
Attentive Multi-Task Deep Reinforcement LearningCode0
Few-shot classification in Named Entity Recognition TaskCode0
Few-Shot Image Recognition With Knowledge TransferCode0
Automatic classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on chest X-ray image: combination of data augmentation methodsCode0
Identifying Misinformation on YouTube through Transcript Contextual Analysis with Transformer ModelsCode0
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video DetectionCode0
Deep Convolutional Neural Networks for Palm Fruit Maturity ClassificationCode0
Deep Convolution Networks for Compression Artifacts ReductionCode0
Feudal Graph Reinforcement LearningCode0
Exploiting the Semantic Knowledge of Pre-trained Text-Encoders for Continual LearningCode0
FedRef: Communication-Efficient Bayesian Fine Tuning with Reference ModelCode0
Fine-Grained Classification for Poisonous Fungi Identification with Transfer LearningCode0
FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain RecommendationCode0
Federated Machine Learning: Concept and ApplicationsCode0
Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things ApplicationCode0
Improved Training for 3D Point Cloud ClassificationCode0
Improved transferability of self-supervised learning models through batch normalization finetuningCode0
Cross Modality Knowledge Distillation for Multi-Modal Aerial View Object ClassificationCode0
Federated Domain Generalization via Prompt Learning and AggregationCode0
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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