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 2326–2350 of 10307 papers

TitleStatusHype
Cross-Dimension Affinity Distillation for 3D EM Neuron SegmentationCode0
Unveiling the Unknown: Unleashing the Power of Unknown to Known in Open-Set Source-Free Domain AdaptationCode0
Self-supervised learning for skin cancer diagnosis with limited training dataCode0
Federated Class-Incremental Learning with New-Class Augmented Self-DistillationCode1
Balanced Multi-modal Federated Learning via Cross-Modal Infiltration—0
FedLED: Label-Free Equipment Fault Diagnosis with Vertical Federated Transfer Learning—0
Weed mapping in multispectral drone imagery using lightweight vision transformersCode1
Multimodal Sentiment Analysis with Missing Modality: A Knowledge-Transfer Approach—0
Any-point Trajectory Modeling for Policy LearningCode2
OmniDialog: An Omnipotent Pre-training Model for Task-Oriented Dialogue System—0
An Integrated Imitation and Reinforcement Learning Methodology for Robust Agile Aircraft Control with Limited Pilot Demonstration Data—0
Soft Contrastive Learning for Time SeriesCode1
Transfer and Alignment Network for Generalized Category DiscoveryCode0
GRSDet: Learning to Generate Local Reverse Samples for Few-shot Object Detection—0
Recursive Distillation for Open-Set Distributed Robot Localization—0
APTv2: Benchmarking Animal Pose Estimation and Tracking with a Large-scale Dataset and BeyondCode1
TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation LearningCode1
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift—0
Knowledge Guided Semi-Supervised Learning for Quality Assessment of User Generated VideosCode0
Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological imagesCode0
Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change DetectionCode1
Learning to Prompt Knowledge Transfer for Open-World Continual LearningCode0
Efficient Discrete Physics-informed Neural Networks for Addressing Evolutionary Partial Differential Equations—0
Bayesian Inverse Transfer in Evolutionary Multiobjective OptimizationCode0
Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification—0
Show:102550
← PrevPage 94 of 413Next →
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