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 7526–7550 of 10307 papers

TitleStatusHype
Transfer learning for multi-center classification of chronic obstructive pulmonary disease—0
Transfer learning for multifidelity simulation-based inference in cosmology—0
Transfer Learning for Multi-lingual Tasks -- a Survey—0
Transfer Learning for Named-Entity Recognition with Neural Networks—0
Transfer Learning for Neural Networks-based Equalizers in Coherent Optical Systems—0
Transfer Learning for Neural Semantic Parsing—0
Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing—0
Transfer learning for nonlinear dynamics and its application to fluid turbulence—0
Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier—0
Transfer Learning for Nonparametric Regression: Non-asymptotic Minimax Analysis and Adaptive Procedure—0
Transfer Learning for Olfactory Object Detection—0
Transfer Learning for Oral Cancer Detection using Microscopic Images—0
Transfer Learning for Personality Perception via Speech Emotion Recognition—0
Transfer Learning for Portfolio Optimization—0
Transfer Learning for Power Outage Detection Task with Limited Training Data—0
Transfer learning for predicting source terms of principal component transport in chemically reactive flow—0
Transfer learning for process design with reinforcement learning—0
Tackling Data Scarcity with Transfer Learning: A Case Study of Thickness Characterization from Optical Spectra of Perovskite Thin Films—0
Transfer Learning for Real-time Deployment of a Screening Tool for Depression Detection Using Actigraphy—0
Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task—0
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning—0
Transfer learning for Remaining Useful Life Prediction Based on Consensus Self-Organizing Models—0
Transfer Learning for Retinal Vascular Disease Detection: A Pilot Study with Diabetic Retinopathy and Retinopathy of Prematurity—0
Transfer Learning for Robust Low-Resource Children's Speech ASR with Transformers and Source-Filter Warping—0
Transfer Learning for Scene Text Recognition in Indian Languages—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