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 7351–7400 of 10307 papers

TitleStatusHype
Transfer Learning for Oral Cancer Detection using Microscopic Images—0
Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data SegmentationCode0
Automatic Recognition of the Supraspinatus Tendinopathy from Ultrasound Images using Convolutional Neural Networks—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
Application of Facial Recognition using Convolutional Neural Networks for Entry Access ControlCode0
Ranking Neural Checkpoints—0
Cost-effective Variational Active Entity Resolution—0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification—0
Efficient Conditional Pre-training for Transfer Learning—0
Interpretable and Transferable Models to Understand the Impact of Lockdown Measures on Local Air QualityCode0
Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation—0
Abnormal Event Detection in Urban Surveillance Videos Using GAN and Transfer Learning—0
Palomino-Ochoa at SemEval-2020 Task 9: Robust System based on Transformer for Code-Mixed Sentiment Classification—0
Continuous Emotion Recognition with Spatiotemporal Convolutional Neural Networks—0
Out-of-Task Training for Dialog State Tracking Models—0
Master Thesis: Neural Sign Language Translation by Learning Tokenization—0
Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation—0
Deep learning models for gastric signet ring cell carcinoma classification in whole slide images—0
A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning—0
Recognition and standardization of cardiac MRI orientation via multi-tasking learning and deep neural networks—0
Can Semantic Labels Assist Self-Supervised Visual Representation Learning?—0
Probing Predictions on OOD Images via Nearest CategoriesCode0
Assistive Diagnostic Tool for Brain Tumor Detection using Computer Vision—0
Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients—0
Refining Automatic Speech Recognition System for older adults—0
Towards All-around Knowledge Transferring: Learning From Task-irrelevant Labels—0
On the Effectiveness of Vision Transformers for Zero-shot Face Anti-SpoofingCode0
A Transfer Learning Based Active Learning Framework for Brain Tumor Classification—0
In-Car driver response classification using Deep Learning (CNN) based Computer VisionCode0
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies—0
Transfer learning of chaotic systems—0
On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision—0
A Study of Domain Generalization on Ultrasound-based Multi-Class Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer Learning—0
Query-based Targeted Action-Space Adversarial Policies on Deep Reinforcement Learning AgentsCode0
Robotic self-representation improves manipulation skills and transfer learning—0
Multi-Modal Emotion Detection with Transfer Learning—0
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study—0
Roof fall hazard detection with convolutional neural networks using transfer learningCode0
A Transfer Learning Framework for Anomaly Detection Using Model of Normality—0
Using IPA-Based Tacotron for Data Efficient Cross-Lingual Speaker Adaptation and Pronunciation Enhancement—0
Transferred Fusion Learning using Skipped Networks—0
Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images—0
Classification of COVID-19 in Chest CT Images using Convolutional Support Vector Machines—0
Generic Semi-Supervised Adversarial Subject Translation for Sensor-Based Human Activity Recognition—0
Recognizing More Emotions with Less Data Using Self-supervised Transfer Learning—0
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning—0
Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes—0
Filtered Manifold Alignment—0
An ensemble-based approach by fine-tuning the deep transfer learning models to classify pneumonia from chest X-ray images—0
Real-Time Decentralized knowledge Transfer at the EdgeCode0
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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