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 301–325 of 10307 papers

TitleStatusHype
An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement LearningCode1
A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species ClassificationCode1
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural RepresentationsCode1
An Empirical Study on Cross-X Transfer for Legal Judgment PredictionCode1
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot LabelsCode1
A New Knowledge Distillation Network for Incremental Few-Shot Surface Defect DetectionCode1
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG ClassificationCode1
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement LearningCode1
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer LearningCode1
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural NetworksCode1
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer LearningCode1
A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive FusionCode1
CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel SynthesisCode1
Class-relation Knowledge Distillation for Novel Class DiscoveryCode1
Chip Placement with Deep Reinforcement LearningCode1
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
Choquet Integral and Coalition Game-based Ensemble of Deep Learning Models for COVID-19 Screening from Chest X-ray ImagesCode1
A Competition Winning Deep Reinforcement Learning Agent in microRTSCode1
An Empirical Analysis of Image-Based Learning Techniques for Malware ClassificationCode1
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric ModelsCode1
ChrEn: Cherokee-English Machine Translation for Endangered Language RevitalizationCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
CEM500K – A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learningCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
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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