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 3051–3075 of 10307 papers

TitleStatusHype
Analysis of Multilingual Sequence-to-Sequence speech recognition systems—0
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning—0
Deep-Learning-Based Markerless Pose Estimation Systems in Gait Analysis: DeepLabCut Custom Training and the Refinement Function—0
A New Mask R-CNN Based Method for Improved Landslide Detection—0
A New Method for Vehicle Logo Recognition Based on Swin Transformer—0
Distilling Generative-Discriminative Representations for Very Low-Resolution Face Recognition—0
An Analysis of Semantically-Aligned Speech-Text Embeddings—0
Blockchain as an Enabler for Transfer Learning in Smart Environments—0
Block Toeplitz Sparse Precision Matrix Estimation for Large-Scale Interval-Valued Time Series Forecasting—0
Distilling Knowledge From a Deep Pose Regressor Network—0
BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning—0
Effective Representations of Clinical Notes—0
Distilling Localization for Self-Supervised Representation Learning—0
Distilling Named Entity Recognition Models for Endangered Species from Large Language Models—0
Distilling Normalizing Flows—0
Distilling Structured Knowledge for Text-Based Relational Reasoning—0
A New Perspective on Smiling and Laughter Detection: Intensity Levels Matter—0
A Deep Value-network Based Approach for Multi-Driver Order Dispatching—0
Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2—0
Distral: Robust Multitask Reinforcement Learning—0
Automating the Surveillance of Mosquito Vectors from Trapped Specimens Using Computer Vision Techniques—0
Deep Learning-Based Image Kernel for Inductive Transfer—0
Automatic Wayang Ontology Construction using Relation Extraction from Free Text—0
Distributed Transfer Learning with 4th Gen Intel Xeon Processors—0
Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients—0
Show:102550
← PrevPage 123 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