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 4321–4330 of 10307 papers

TitleStatusHype
CULL-MT: Compression Using Language and Layer pruning for Machine Translation—0
Cued Speech Generation Leveraging a Pre-trained Audiovisual Text-to-Speech Model—0
Audiovisual transfer learning for audio tagging and sound event detection—0
Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy—0
A Methodology for Controlling the Emotional Expressiveness in Synthetic Speech -- a Deep Learning approach—0
Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions—0
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing—0
CtlGAN: Few-shot Artistic Portraits Generation with Contrastive Transfer Learning—0
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement—0
A Method of Augmenting Bilingual Terminology by Taking Advantage of the Conceptual Systematicity of Terminologies—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