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 6851–6875 of 10307 papers

TitleStatusHype
Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge—0
One Model to Rule them All: Towards Zero-Shot Learning for Databases—0
Prediction of clinical tremor severity using Rank Consistent Ordinal Regression—0
Adapting CRISP-DM for Idea Mining: A Data Mining Process for Generating Ideas Using a Textual Dataset—0
GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition—0
Investigation of Transfer Languages for Parsing Latin: Italic Branch vs. Hellenic Branch—0
MRCBert: A Machine Reading ComprehensionApproach for Unsupervised SummarizationCode0
COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images—0
A Deep Learning Framework for Lifelong Machine Learning—0
Towards cross-lingual application of language-specific PoS tagging schemes—0
Cross-lingual hate speech detection based on multilingual domain-specific word embeddings—0
Crackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolitional Neural Networks—0
Convolutional neural networks for Alzheimer’s disease detection on MRI imagesCode0
Generalization Guarantees for Neural Architecture Search with Train-Validation Split—0
Spirit Distillation: A Model Compression Method with Multi-domain Knowledge Transfer—0
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual RepresentationsCode0
Transfer Learning on Multi-Fidelity Data—0
Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural NetworkCode0
Multi-Task Learning of Query Intent and Named Entities using Transfer Learning—0
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis—0
A Deep Transfer Learning-based Edge Computing Method for Home Health Monitoring—0
Machine Learning Algorithms for Breast Cancer Detection in Mammography Images: A Comparative Study—0
Evaluating the Values of Sources in Transfer LearningCode0
Improving Botnet Detection with Recurrent Neural Network and Transfer Learning—0
Towards Sustainable Census Independent Population Estimation in Mozambique—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