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

Showing 25512575 of 10307 papers

TitleStatusHype
Fine-Grained Classification for Poisonous Fungi Identification with Transfer LearningCode0
Finger Pose Estimation for Under-screen Fingerprint SensorCode0
Food Classification with Convolutional Neural Networks and Multi-Class Linear Discernment AnalysisCode0
Hi-gMISnet: generalized medical image segmentation using DWT based multilayer fusion and dual mode attention into high resolution pGANCode0
Few-shot classification in Named Entity Recognition TaskCode0
HintNet: Hierarchical Knowledge Transfer Networks for Traffic Accident Forecasting on Heterogeneous Spatio-Temporal DataCode0
Decoding Neural Responses in Mouse Visual Cortex through a Deep Neural NetworkCode0
Histogram-based Parameter-efficient Tuning for Passive Sonar ClassificationCode0
Few-Shot Fruit Segmentation via Transfer LearningCode0
Feudal Graph Reinforcement LearningCode0
Few-shot calibration of low-cost air pollution (PM2.5) sensors using meta-learningCode0
FedRef: Communication-Efficient Bayesian Fine Tuning with Reference ModelCode0
Automated tabulation of clinical trial results: A joint entity and relation extraction approach with transformer-based language representationsCode0
How Language-Neutral is Multilingual BERT?Code0
Cross-project Defect Prediction with An Enhanced Transfer Boosting AlgorithmCode0
Decoupled Self Attention for Accurate One Stage Object DetectionCode0
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
Attentive Multi-Task Deep Reinforcement LearningCode0
Federated Domain Generalization via Prompt Learning and AggregationCode0
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video DetectionCode0
Federated Continual Graph LearningCode0
Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning TechniquesCode0
Federated Continual Learning for Text Classification via Selective Inter-client TransferCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2Unverified
2DFA-ENTAccuracy69.2Unverified
3DFA-SAFNAccuracy69.1Unverified
4EasyTLAccuracy63.3Unverified
5MEDAAccuracy60.3Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95Unverified