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 8251–8300 of 10307 papers

TitleStatusHype
Durocmien: A deep framework for duroc skeleton extraction in constraint environment—0
Model-Driven Beamforming Neural Networks—0
Driver Safety Development Real Time Driver Drowsiness Detection System Based on Convolutional Neural Network—0
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning—0
Towards detection and classification of microscopic foraminifera using transfer learningCode0
Boosting Deep Face Recognition via Disentangling Appearance and Geometry—0
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models—0
Multi-Scale Weight Sharing Network for Image Recognition—0
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data—0
To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers—0
Multipurpose Intelligent Process Automation via Conversational Assistant—0
SUR-FeatNet: Predicting the Satisfied User Ratio Curvefor Image Compression with Deep Feature LearningCode0
Multitask learning over graphs: An Approach for Distributed, Streaming Machine Learning—0
Generalizing Emergent Communication—0
Exploring Benefits of Transfer Learning in Neural Machine Translation—0
Domain Adaptation via Teacher-Student Learning for End-to-End Speech Recognition—0
COPD Classification in CT Images Using a 3D Convolutional Neural Network—0
A Comprehensive Survey of Multilingual Neural Machine Translation—0
A Two stage Adaptive Knowledge Transfer Evolutionary Multi-tasking Based on Population Distribution for Multi/Many-Objective Optimization—0
Decomposable Probability-of-Success Metrics in Algorithmic Search—0
On the comparability of Pre-trained Language Models—0
Inter- and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition—0
DeepBeat: A multi-task deep learning approach to assess signal quality and arrhythmia detection in wearable devices—0
Generative Adversarial Networks For Data Scarcity Industrial Positron Images With Attention—0
Meta Variance Transfer: Learning to Augment from the Others—0
Learning Attentive Meta-Transfer—0
Mutual Transfer Learning for Massive Data—0
Estimating Q(s,s') with Deterministic Dynamics Gradients—0
Homogeneous Online Transfer Learning with Online Distribution Discrepancy MinimizationCode0
Machine Learning based Post Processing Artifact Reduction in HEVC Intra Coding—0
Prediction of wall-bounded turbulence from wall quantities using convolutional neural networks—0
Quantifying the Performance of Federated Transfer Learning—0
Deep neural network models for computational histopathology: A survey—0
Improved Multi-Stage Training of Online Attention-based Encoder-Decoder Models—0
Transfer Learning for Brain Tumor Segmentation—0
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative StudyCode0
Transfer Learning in General Lensless Imaging through Scattering Media—0
Towards Deep Federated Defenses Against Malware in Cloud Ecosystems—0
Deep Transfer Learning Based Downlink Channel Prediction for FDD Massive MIMO SystemsCode0
Neural Subgraph Isomorphism CountingCode0
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer—0
Intelligent Condition Based Monitoring Techniques for Bearing Fault Diagnosis—0
Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data—0
Data-Free Adversarial DistillationCode0
Transfer Learning with Edge Attention for Prostate MRI Segmentation—0
Progressive transfer learning for low frequency data prediction in full waveform inversion—0
Destruction of Image Steganography using Generative Adversarial NetworksCode0
Image Analytics for Legal Document Review: A Transfer Learning Approach—0
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning—0
Integration of Convolutional Neural Networks for Pulmonary Nodule Malignancy Assessment in a Lung Cancer Classification Pipeline—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