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 8876–8900 of 10307 papers

TitleStatusHype
Automatic Online Multi-Source Domain AdaptationCode0
Automaton-Guided Curriculum Generation for Reinforcement Learning AgentsCode0
Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer LearningCode0
Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learningCode0
AutoTransfer: AutoML with Knowledge Transfer -- An Application to Graph Neural NetworksCode0
Auto-Transfer: Learning to Route Transferrable RepresentationsCode0
A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge TransferCode0
Avicenna: a challenge dataset for natural language generation toward commonsense syllogistic reasoningCode0
A Visual Domain Transfer Learning Approach for Heartbeat Sound ClassificationCode0
A Wander Through the Multimodal Landscape: Efficient Transfer Learning via Low-rank Sequence Multimodal AdapterCode0
A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial DiversityCode0
Balanced joint maximum mean discrepancy for deep transfer learningCode0
BanglaNLP at BLP-2023 Task 2: Benchmarking different Transformer Models for Sentiment Analysis of Bangla Social Media PostsCode0
BatSort: Enhanced Battery Classification with Transfer Learning for Battery Sorting and RecyclingCode0
BatStyler: Advancing Multi-category Style Generation for Source-free Domain GeneralizationCode0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation ProblemsCode0
Bayesian Multi-Task Transfer Learning for Soft Prompt TuningCode0
Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interactionCode0
Deep State Inference: Toward Behavioral Model Inference of Black-box Software SystemsCode0
Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset EvaluationCode0
Benchmarking histopathology foundation models in a multi-center dataset for skin cancer subtypingCode0
Benchmarking Representation Learning for Natural World Image CollectionsCode0
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve OptimizationCode0
Bengali Handwritten Character Classification using Transfer Learning on Deep Convolutional Neural NetworkCode0
BertaQA: How Much Do Language Models Know About Local Culture?Code0
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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