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 8101–8150 of 10307 papers

TitleStatusHype
Forecasting adverse surgical events using self-supervised transfer learning for physiological signals—0
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space—0
x-vectors meet emotions: A study on dependencies between emotion and speaker recognition—0
Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling—0
Optimal Transfer Learning Model for Binary Classification of Funduscopic Images through Simple Heuristics—0
Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial OptimizationCode1
2.75D: Boosting learning by representing 3D Medical imaging to 2D features for small dataCode0
On transfer learning of neural networks using bi-fidelity data for uncertainty propagation—0
Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer LearningCode0
Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson's Disease from Speech in Three Different Languages—0
Localized Flood DetectionWith Minimal Labeled Social Media Data Using Transfer Learning—0
Classification Algorithm of Speech Data of Parkinsons Disease Based on Convolution Sparse Kernel Transfer Learning with Optimal Kernel and Parallel Sample Feature Selection—0
Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration—0
GradMix: Multi-source Transfer across Domains and Tasks—0
MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI DataCode1
Unlabeled Data Deployment for Classification of Diabetic Retinopathy Images Using Knowledge Transfer—0
Understanding the Automated Parameter Optimization on Transfer Learning for CPDP: An Empirical StudyCode1
CIFAR-10 Image Classification Using Feature EnsemblesCode0
Renofeation: A Simple Transfer Learning Method for Improved Adversarial RobustnessCode1
Geometric Dataset Distances via Optimal TransportCode1
Student/Teacher Advising through Reward Augmentation—0
Finding Quantum Critical Points with Neural-Network Quantum States—0
Conditional Deep Gaussian Processes: multi-fidelity kernel learningCode0
Multilingual acoustic word embedding models for processing zero-resource languagesCode1
Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach—0
The Costs and Benefits of Goal-Directed Attention in Deep Convolutional Neural Networks—0
Extracting dispersion curves from ambient noise correlations using deep learning—0
Transfer Learning for HVAC System Fault DetectionCode0
Classification of Chest Diseases using Wavelet Transforms and Transfer Learning—0
Neural Sign Language Translation by Learning Tokenization—0
Continuous Emotion Recognition via Deep Convolutional Autoencoder and Support Vector Regressor—0
Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering TasksCode1
ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs—0
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications—0
Near real-time map building with multi-class image set labelling and classification of road conditions using convolutional neural networks—0
Siamese Content Loss Networks for Highly Imbalanced Medical Image Segmentation—0
3D-RADNet: Extracting labels from DICOM metadata for training general medical domain deep 3D convolution neural networks—0
Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings—0
Modular network for high accuracy object detection—0
A Study of the Tasks and Models in Machine Reading Comprehension—0
AutoFCL: Automatically Tuning Fully Connected Layers for Handling Small DatasetCode0
ManyModalQA: Modality Disambiguation and QA over Diverse InputsCode1
Automatic phantom test pattern classification through transfer learning with deep neural networks—0
Transfer Learning using Neural Ordinary Differential Equations—0
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications—0
Heterogeneous Transfer Learning in Ensemble Clustering—0
GTNet: Generative Transfer Network for Zero-Shot Object DetectionCode0
A Transfer Learning Approach to Cross-Modal Object Recognition: From Visual Observation to Robotic Haptic Exploration—0
Durocmien: A deep framework for duroc skeleton extraction in constraint environment—0
Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural NetworkCode1
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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