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 8876–8900 of 10307 papers

TitleStatusHype
Additional Positive Enables Better Representation Learning for Medical Images—0
SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
Progressive trajectory matching for medical dataset distillation—0
Progressive transfer learning for low frequency data prediction in full waveform inversion—0
Progressive Transfer Learning for Multi-Pass Fundus Image Restoration—0
Surprise Language Challenge: Developing a Neural Machine Translation System between Pashto and English in Two Months—0
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features—0
Adding more data does not always help: A study in medical conversation summarization with PEGASUS—0
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research—0
The role of ego vision in view-invariant action recognition—0
​4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection—0
Prompted Meta-Learning for Few-shot Knowledge Graph Completion—0
Ada-VSR: Adaptive Video Super-Resolution with Meta-Learning—0
Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control—0
AdaVocoder: Adaptive Vocoder for Custom Voice—0
AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression—0
Prompting Large Language Model for Machine Translation: A Case Study—0
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data—0
A Dataset of Offensive Language in Kosovo Social Media—0
Surveying You Only Look Once (YOLO) Multispectral Object Detection Advancements, Applications And Challenges—0
A Dataset for Sanskrit Word Segmentation—0
Propagation-aware Social Recommendation by Transfer Learning—0
Proper Reuse of Image Classification Features Improves Object Detection—0
Survival and grade of the glioma prediction using transfer learning—0
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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