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

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Showing 7001–7050 of 10307 papers

TitleStatusHype
Palomino-Ochoa at SemEval-2020 Task 9: Robust System based on Transformer for Code-Mixed Sentiment Classification—0
EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP ApplicationsCode1
Assistive Diagnostic Tool for Brain Tumor Detection using Computer Vision—0
Probing Predictions on OOD Images via Nearest CategoriesCode0
Can Semantic Labels Assist Self-Supervised Visual Representation Learning?—0
Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients—0
Refining Automatic Speech Recognition System for older adults—0
Recognition and standardization of cardiac MRI orientation via multi-tasking learning and deep neural networks—0
Towards All-around Knowledge Transferring: Learning From Task-irrelevant Labels—0
In-Car driver response classification using Deep Learning (CNN) based Computer VisionCode0
A Transfer Learning Based Active Learning Framework for Brain Tumor Classification—0
On the Effectiveness of Vision Transformers for Zero-shot Face Anti-SpoofingCode0
Transfer learning of chaotic systems—0
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies—0
On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision—0
Query-based Targeted Action-Space Adversarial Policies on Deep Reinforcement Learning AgentsCode0
Multi-Modal Emotion Detection with Transfer Learning—0
A Study of Domain Generalization on Ultrasound-based Multi-Class Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer Learning—0
Robotic self-representation improves manipulation skills and transfer learning—0
Roof fall hazard detection with convolutional neural networks using transfer learningCode0
A Transfer Learning Framework for Anomaly Detection Using Model of Normality—0
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study—0
Using IPA-Based Tacotron for Data Efficient Cross-Lingual Speaker Adaptation and Pronunciation Enhancement—0
Generic Semi-Supervised Adversarial Subject Translation for Sensor-Based Human Activity Recognition—0
Filtered Manifold Alignment—0
Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images—0
An ensemble-based approach by fine-tuning the deep transfer learning models to classify pneumonia from chest X-ray images—0
Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes—0
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning—0
Classification of COVID-19 in Chest CT Images using Convolutional Support Vector Machines—0
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANsCode1
Real-Time Decentralized knowledge Transfer at the EdgeCode0
Recognizing More Emotions with Less Data Using Self-supervised Transfer Learning—0
Transferred Fusion Learning using Skipped Networks—0
Deep Transfer Learning-Assisted Signal Detection for Ambient Backscatter Communications—0
A Transfer Learning Approach for Dialogue Act Classification of GitHub Issue CommentsCode0
Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer LearningCode1
Detecting Social Media Manipulation in Low-Resource Languages—0
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning—0
Low-Resource Adaptation of Neural NLP Models—0
PAMS: Quantized Super-Resolution via Parameterized Max ScaleCode1
Learning Generalizable Physiological Representations from Large-scale Wearable DataCode1
Predictive Analysis of Diabetic Retinopathy with Transfer Learning—0
Multi-Temporal Convolutions for Human Action Recognition in VideosCode1
Robustness and Diversity Seeking Data-Free Knowledge DistillationCode0
Exploring Multimodal Features and Fusion Strategies for Analyzing Disaster Tweets—0
Domain Adaptive Person Re-Identification via Coupling OptimizationCode0
Deep Transfer Learning for Automated Diagnosis of Skin Lesions from PhotographsCode0
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning—0
Intra-Domain Task-Adaptive Transfer Learning to Determine Acute Ischemic Stroke Onset Time—0
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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