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 6176–6200 of 10307 papers

TitleStatusHype
A Review of Deep Learning Approaches for Non-Invasive Cognitive Impairment Detection—0
A Survey of Fish Tracking Techniques Based on Computer Vision—0
A Corpus for Commonsense Inference in Story Cloze Test—0
Huawei's NMT Systems for the WMT 2019 Biomedical Translation Task—0
Huawei’s Submissions to the WMT20 Biomedical Translation Task—0
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models—0
Self-Supervised Representation Learning From Multi-Domain Data—0
Human-AI Teaming Using Large Language Models: Boosting Brain-Computer Interfacing (BCI) and Brain Research—0
A Review of Automated Diagnosis of COVID-19 Based on Scanning Images—0
Human-centric Transfer Learning Explanation via Knowledge Graph [Extended Abstract]—0
Human experts vs. machines in taxa recognition—0
Human Gender Prediction Based on Deep Transfer Learning from Panoramic Radiograph Images—0
Self-Supervised Representation Learning from Temporal Ordering of Automated Driving Sequences—0
A Quantile-based Approach for Hyperparameter Transfer Learning—0
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text—0
Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation—0
Human Recognition Using Face in Computed Tomography—0
Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios—0
Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles—0
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning—0
Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation—0
HUST bearing: a practical dataset for ball bearing fault diagnosis—0
HWNet v2: An Efficient Word Image Representation for Handwritten Documents—0
HW-TSC’s Participation at WMT 2020 Quality Estimation Shared Task—0
Hybrid Classical-Quantum Deep Learning Models for Autonomous Vehicle Traffic Image Classification Under Adversarial Attack—0
Show:102550
← PrevPage 248 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