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 6901–6950 of 10307 papers

TitleStatusHype
WiFiNet: WiFi-based indoor localisation using CNNs—0
Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling—0
Transfer Learning for Neural Networks-based Equalizers in Coherent Optical Systems—0
Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining—0
Detecting False Data Injection Attacks in Smart Grids with Modeling Errors: A Deep Transfer Learning Based ApproachCode0
eGAN: Unsupervised approach to class imbalance using transfer learningCode0
The NTNU Taiwanese ASR System for Formosa Speech Recognition Challenge 2020—0
Grapheme-to-Phoneme Transformer Model for Transfer Learning Dialects—0
A transfer-learning approach for lesion detection in endoscopic images from the urinary tract—0
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays—0
Post-Hoc Domain Adaptation via Guided Data HomogenizationCode0
Analysis Towards Classification of Infection and Ischaemia of Diabetic Foot Ulcers—0
Tuned Compositional Feature Replays for Efficient Stream LearningCode0
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark—0
Adaptive Variants of Optimal Feedback Policies—0
A Concise Review of Transfer Learning—0
Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition—0
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network—0
Efficient Personalized Speech Enhancement through Self-Supervised Learning—0
Graph Sampling Based Deep Metric Learning for Generalizable Person Re-Identification—0
TATL: Task Agnostic Transfer Learning for Skin Attributes Detection—0
COVID-19 Detection in Cough, Breath and Speech using Deep Transfer Learning and Bottleneck Features—0
On the Pitfalls of Learning with Limited Data: A Facial Expression Recognition Case Study—0
Using GPT-2 to Create Synthetic Data to Improve the Prediction Performance of NLP Machine Learning Classification Models—0
Towards Offensive Language Identification for Dravidian LanguagesCode0
Whit’s the Richt Pairt o Speech: PoS tagging for Scots—0
GCDH@LT-EDI-EACL2021: XLM-RoBERTa for Hope Speech Detection in English, Malayalam, and Tamil—0
IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian LanguagesCode0
Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models—0
MIDAS: A Dialog Act Annotation Scheme for Open Domain HumanMachine Spoken Conversations—0
EDIOne@LT-EDI-EACL2021: Pre-trained Transformers with Convolutional Neural Networks for Hope Speech Detection.—0
LA-SACo: A Study of Learning Approaches for Sentiments Analysis inCode-Mixing Texts—0
Offensive language identification in Dravidian code mixed social media text—0
Keep Learning: Self-supervised Meta-learning for Learning from Inference—0
On the Hidden Negative Transfer in Sequential Transfer Learning for Domain Adaptation from News to Tweets—0
Low-Resource Neural Machine Translation for Southern African Languages—0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
Cross-Lingual Transfer Learning for Hate Speech Detection—0
LIFT-SLAM: a deep-learning feature-based monocular visual SLAM method—0
DeepMI: Deep Multi-lead ECG Fusion for Identifying Myocardial Infarction and its Occurrence-time—0
DA-DETR: Domain Adaptive Detection Transformer with Information Fusion—0
Drowsiness Detection Based On Driver Temporal Behavior Using a New Developed Dataset—0
Transfer Learning for Node Regression Applied to Spreading PredictionCode0
Zero-Shot Language Transfer vs Iterative Back Translation for Unsupervised Machine TranslationCode0
Automated Cleanup of the ImageNet Dataset by Model Consensus, Explainability and Confident LearningCode0
Benchmarking Representation Learning for Natural World Image CollectionsCode0
A resource-efficient method for repeated HPO and NAS problems—0
Source-Free Domain Adaptation for Semantic Segmentation—0
Robust Audio-Visual Instance Discrimination—0
Zero-shot Adversarial Quantization—0
Show:102550
← PrevPage 139 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