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 326–350 of 10307 papers

TitleStatusHype
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional FiltersCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
CLiMB: A Continual Learning Benchmark for Vision-and-Language TasksCode1
A Data-Based Perspective on Transfer LearningCode1
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer LearningCode1
Class-relation Knowledge Distillation for Novel Class DiscoveryCode1
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural NetworksCode1
An Empirical Analysis of Image-Based Learning Techniques for Malware ClassificationCode1
A Data-Efficient Pan-Tumor Foundation Model for Oncology CT InterpretationCode1
An Empirical Study on Cross-X Transfer for Legal Judgment PredictionCode1
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer LearningCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set FrameworkCode1
A Broader Study of Cross-Domain Few-Shot LearningCode1
An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature SelectionCode1
A New Knowledge Distillation Network for Incremental Few-Shot Surface Defect DetectionCode1
CloudS2Mask: A novel deep learning approach for improved cloud and cloud shadow masking in Sentinel-2 imageryCode1
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG ClassificationCode1
An Improved Person Re-identification Method by light-weight convolutional neural networkCode1
CLIP-Lite: Information Efficient Visual Representation Learning with Language SupervisionCode1
A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive FusionCode1
Annealing-Based Label-Transfer Learning for Open World Object DetectionCode1
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance ComputingCode1
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement LearningCode1
Choquet Integral and Coalition Game-based Ensemble of Deep Learning Models for COVID-19 Screening from Chest X-ray ImagesCode1
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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