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 6576–6600 of 10307 papers

TitleStatusHype
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter—0
Multilingual Speech Translation from Efficient Finetuning of Pretrained Models—0
Surprise Language Challenge: Developing a Neural Machine Translation System between Pashto and English in Two Months—0
Exploring Cross-Lingual Transfer Learning with Unsupervised Machine Translation—0
Recursive Tree-Structured Self-Attention for Answer Sentence Selection—0
Neural Machine Translation in Low-Resource Setting: a Case Study in English-Marathi Pair—0
Revisiting Pretraining with Adapters—0
Extracting Events from Industrial Incident Reports—0
JUST-BLUE at SemEval-2021 Task 1: Predicting Lexical Complexity using BERT and RoBERTa Pre-trained Language Models—0
Make the Blind Translator See The World: A Novel Transfer Learning Solution for Multimodal Machine Translation—0
Conditional Bures Metric for Domain Adaptation—0
Adaptable image quality assessment using meta-reinforcement learning of task amenability—0
Addressing materials' microstructure diversity using transfer learning—0
Malware Classification Using Transfer Learning—0
Using transfer learning to study burned area dynamics: A case study of refugee settlements in West Nile, Northern Uganda—0
A Visual Domain Transfer Learning Approach for Heartbeat Sound ClassificationCode0
Graph Constrained Data Representation Learning for Human Motion SegmentationCode0
Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network—0
Transfer Learning in Electronic Health Records through Clinical Concept Embedding—0
Transferable Knowledge-Based Multi-Granularity Aggregation Network for Temporal Action Localization: Submission to ActivityNet Challenge 2021—0
Toward Co-creative Dungeon Generation via Transfer Learning—0
Fine-Grained Emotion Prediction by Modeling Emotion DefinitionsCode0
Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue ImagingCode0
Preliminary Steps Towards Federated Sentiment Classification—0
Deep Transfer Clustering of Radio Signals—0
Show:102550
← PrevPage 264 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