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 3701–3725 of 10307 papers

TitleStatusHype
Exo2EgoDVC: Dense Video Captioning of Egocentric Procedural Activities Using Web Instructional Videos—0
ExoMiner++: Enhanced Transit Classification and a New Vetting Catalog for 2-Minute TESS Data—0
Deep CNNs for large scale species classification—0
Expanding Expressiveness of Diffusion Models with Limited Data via Self-Distillation based Fine-Tuning—0
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms—0
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks—0
Federated Distillation: A Survey—0
Federated Graph Learning with Graphless Clients—0
Deep Clustering of Remote Sensing Scenes through Heterogeneous Transfer Learning—0
Automatic Audio Captioning using Attention weighted Event based Embeddings—0
A multi-objective perspective on jointly tuning hardware and hyperparameters—0
Adaptive Transfer Learning of Multi-View Time Series Classification—0
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation—0
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning—0
DeepBeat: A multi-task deep learning approach to assess signal quality and arrhythmia detection in wearable devices—0
CLUE: Contextualised Unified Explainable Learning of User Engagement in Video Lectures—0
Explainable AI based Glaucoma Detection using Transfer Learning and LIME—0
Explainable AI for Fair Sepsis Mortality Predictive Model—0
Deep Bag-of-Sub-Emotions for Depression Detection in Social Media—0
Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability—0
Explainable AI in Handwriting Detection for Dyslexia Using Transfer Learning—0
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning—0
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine—0
Explainable Lung Disease Classification from Chest X-Ray Images Utilizing Deep Learning and XAI—0
Automatically Score Tissue Images Like a Pathologist by Transfer Learning—0
Show:102550
← PrevPage 149 of 413Next →
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