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 4401–4450 of 10307 papers

TitleStatusHype
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images—0
Transfer learning for self-supervised, blind-spot seismic denoising—0
Transfer Learning for sEMG-based Hand Gesture Classification using Deep Learning in a Master-Slave Architecture—0
Transfer Learning for Sequence Labeling Using Source Model and Target Data—0
Transfer Learning for Sequences via Learning to Collocate—0
Transfer Learning for Spatial Autoregressive Models with Application to U.S. Presidential Election Prediction—0
Transfer Learning for Speech and Language Processing—0
Transfer Learning for Structured Pruning under Limited Task Data—0
Transfer learning for tensor Gaussian graphical models—0
Transfer Learning for Text Diffusion Models—0
Transfer Learning for the Prediction of Entity Modifiers in Clinical Text: Application to Opioid Use Disorder Case Detection—0
Transfer Learning for Thermal Comfort Prediction in Multiple Cities—0
Transfer Learning for Transient Classification: From Simulations to Real Data and ZTF to LSST—0
Transfer Learning for Ultrasound Tongue Contour Extraction with Different Domains—0
Transfer Learning for Underrepresented Music Generation—0
Transfer-learning for video classification: Video Swin Transformer on multiple domains—0
Transfer Learning for Video Recognition with Scarce Training Data for Deep Convolutional Neural Network—0
Transfer Learning Framework for Low-Resource Text-to-Speech using a Large-Scale Unlabeled Speech Corpus—0
Transfer Learning from Adult to Children for Speech Recognition: Evaluation, Analysis and Recommendations—0
Transfer Learning from an Artificial Radiograph-landmark Dataset for Registration of the Anatomic Skull Model to Dual Fluoroscopic X-ray Images—0
Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection—0
Transfer Learning from Audio-Visual Grounding to Speech Recognition—0
Transfer learning from first-principles calculations to experiments with chemistry-informed domain transformation—0
Transfer learning from High-Resource to Low-Resource Language Improves Speech Affect Recognition Classification Accuracy—0
Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter—0
Transfer Learning from Partial Annotations for Whole Brain Segmentation—0
Transfer Learning from Pre-trained BERT for Pronoun Resolution—0
Transfer Learning from Pre-trained Language Models Improves End-to-End Speech Summarization—0
Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection—0
Transfer Learning From Sound Representations For Anger Detection in Speech—0
Transfer Learning from Synthetic In-vitro Soybean Pods Dataset for In-situ Segmentation of On-branch Soybean Pod—0
Transfer Learning From Synthetic To Real Images Using Variational Autoencoders For Precise Position Detection—0
Transfer learning from synthetic to real images using variational autoencoders for robotic applications—0
Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task—0
Transfer Learning from Whisper for Microscopic Intelligibility Prediction—0
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations—0
Transfer Learning Guided Noise Reduction for Automatic Modulation Classification—0
Transfer Learning Improves French Cross-Domain Dialect Identification: NRC @ VarDial 2022—0
Transfer Learning improves MI BCI models classification accuracy in Parkinson's disease patients—0
Transfer Learning in 4D for Breast Cancer Diagnosis using Dynamic Contrast-Enhanced Magnetic Resonance Imaging—0
Transfer Learning in Astronomy: A New Machine-Learning Paradigm—0
Transfer Learning in a Transductive Setting—0
Transfer Learning in Bandits with Latent Continuity—0
Transfer Learning in Biomedical Named Entity Recognition: An Evaluation of BERT in the PharmaCoNER task—0
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders—0
Transfer Learning in CNNs Using Filter-Trees—0
Transfer Learning in Conversational Analysis through Reusing Preprocessing Data as Supervisors—0
Transfer Learning in Deep Reinforcement Learning: A Survey—0
Transfer Learning In Differential Privacy's Hybrid-Model—0
Transfer Learning in Electronic Health Records through Clinical Concept Embedding—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