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 9101–9150 of 10307 papers

TitleStatusHype
High Quality Monocular Depth Estimation via Transfer LearningCode1
Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching—0
Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling—0
Predicting with Proxies: Transfer Learning in High Dimension—0
Low Latency Privacy Preserving InferenceCode0
Motion Blur removal via Coupled Autoencoder—0
Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification—0
Temporal Hockey Action Recognition via Pose and Optical Flows—0
An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction—0
Transfer Learning in Astronomy: A New Machine-Learning Paradigm—0
A General Approach to Domain Adaptation with Applications in Astronomy—0
Deep Metric Transfer for Label Propagation with Limited Annotated DataCode0
Optimizing Quantum Error Correction Codes with Reinforcement Learning—0
LORM: Learning to Optimize for Resource Management in Wireless Networks with Few Training Samples—0
Deep Transfer Learning for Static Malware ClassificationCode0
Training on the test set? An analysis of Spampinato et al. [arXiv:1609.00344]—0
FDSNet: Finger dorsal image spoof detection network using light field camera—0
Domain Adaptation for Reinforcement Learning on the Atari—0
TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set—0
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders—0
Deep UL2DL: Channel Knowledge Transfer from Uplink to DownlinkCode0
PAC Learning Guarantees Under Covariate Shift—0
Action Quality Assessment Across Multiple ActionsCode0
Few-shot classification in Named Entity Recognition TaskCode0
Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingCode0
Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation—0
Transfer learning to model inertial confinement fusion experiments—0
When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets—0
Dynamic Transfer Learning for Named Entity Recognition—0
Towards Ophthalmologist Level Accurate Deep Learning System for OCT Screening and Diagnosis—0
Transfer Learning using Representation Learning in Massive Open Online Courses—0
Considering Race a Problem of Transfer Learning—0
ECG Arrhythmia Classification Using Transfer Learning from 2-Dimensional Deep CNN Features—0
Few-Shot Learning via Embedding Adaptation with Set-to-Set FunctionsCode1
Secure Federated Transfer Learning—0
Efficient transfer learning and online adaptation with latent variable models for continuous control—0
Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models—0
PIRC Net : Using Proposal Indexing, Relationships and Context for Phrase Grounding—0
Meta-Transfer Learning for Few-Shot LearningCode1
A Survey of Unsupervised Deep Domain AdaptationCode0
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation—0
Disjoint Label Space Transfer Learning with Common Factorised Space—0
An Embarrassingly Simple Approach for Knowledge DistillationCode0
ADARES: Adaptive Resource Management for Virtual Machines—0
Channel-wise pruning of neural networks with tapering resource constraint—0
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning—0
Playing Text-Adventure Games with Graph-Based Deep Reinforcement LearningCode0
Feasibility of Colon Cancer Detection in Confocal Laser Microscopy Images Using Convolution Neural Networks—0
Bag of Tricks for Image Classification with Convolutional Neural NetworksCode1
A novel database of Children's Spontaneous Facial Expressions (LIRIS-CSE)—0
Show:102550
← PrevPage 183 of 207Next →
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