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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2376–2400 of 10307 papers

TitleStatusHype
BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning—0
Block Toeplitz Sparse Precision Matrix Estimation for Large-Scale Interval-Valued Time Series Forecasting—0
A new method using deep transfer learning on ECG to predict the response to cardiac resynchronization therapy—0
Blockchain as an Enabler for Transfer Learning in Smart Environments—0
A New Method for Vehicle Logo Recognition Based on Swin Transformer—0
A Deep Transfer Learning Method for Cross-Lingual Natural Language Inference—0
A Computer Vision Application for Assessing Facial Acne Severity from Selfie Images—0
Deep Learning for Screening COVID-19 using Chest X-Ray Images—0
A New Mask R-CNN Based Method for Improved Landslide Detection—0
A Big Data-empowered System for Real-time Detection of Regional Discriminatory Comments on Vietnamese Social Media—0
Blessing of Class Diversity in Pre-training—0
A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding—0
A Deep Transfer Learning-based Edge Computing Method for Home Health Monitoring—0
Deep Learning for Motion Classification in Ankle Exoskeletons Using Surface EMG and IMU Signals—0
A Deep Reinforcement Learning Approach for Audio-based Navigation and Audio Source Localization in Multi-speaker Environments—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
A New GAN-based End-to-End TTS Training Algorithm—0
A Computational Model of Inclusive Pedagogy: From Understanding to Application—0
Deep Learning for Over-the-Air Non-Orthogonal Signal Classification—0
A New Deep Boosted CNN and Ensemble Learning based IoT Malware Detection—0
A Computational Approach to Understand Mental Health from Reddit: Knowledge-aware Multitask Learning Framework—0
BIRD: Behavior Induction via Representation-structure Distillation—0
BIOWISH: Biometric Recognition using Wearable Inertial Sensors detecting Heart Activity—0
A Deep Q-Network for the Beer Game: A Deep Reinforcement Learning algorithm to Solve Inventory Optimization Problems—0
Deep Learning for Large-Scale Real-World ACARS and ADS-B Radio Signal Classification—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