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 9251–9300 of 10307 papers

TitleStatusHype
Deep Transfer Learning for WiFi Localization—0
Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images—0
Deep Transfer Learning: Model Framework and Error Analysis—0
Deep Transfer Learning on Satellite Imagery Improves Air Quality Estimates in Developing Nations—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—0
Deep Transfer Learning with Joint Adaptation Networks—0
Deep Transfer Learning with Ridge Regression—0
Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application—0
Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning—0
Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models—0
DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes—0
DeepVIVONet: Using deep neural operators to optimize sensor locations with application to vortex-induced vibrations—0
Deep Zero-Shot Learning for Scene Sketch—0
DeeSIL: Deep-Shallow Incremental Learning—0
DEEVA: A Deep Learning and IoT Based Computer Vision System to Address Safety and Security of Production Sites in Energy Industry—0
Defect Analysis of 3D Printed Cylinder Object Using Transfer Learning Approaches—0
Defeating Misclassification Attacks Against Transfer Learning—0
Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising—0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
Defining Image Memorability using the Visual Memory Schema—0
Deformable-Detection Transformer for Microbubble Localization in Ultrasound Localization Microscopy—0
DeFungi: Direct Mycological Examination of Microscopic Fungi Images—0
Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia—0
Delivery Issues Identification from Customer Feedback Data—0
Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning—0
Demographic Bias in Presentation Attack Detection of Iris Recognition Systems—0
Demonstration of a Standalone, Descriptive, and Predictive Digital Twin of a Floating Offshore Wind Turbine—0
DemoSG: Demonstration-enhanced Schema-guided Generation for Low-resource Event Extraction—0
Demystifying BERT: Implications for Accelerator Design—0
De-novo Chemical Reaction Generation by Means of Temporal Convolutional Neural Networks—0
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays—0
Dense Classification and Implanting for Few-Shot Learning—0
Dense Pixel-Labeling for Reverse-Transfer and Diagnostic Learning on Lung Ultrasound for COVID-19 and Pneumonia Detection—0
Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach—0
Dependency Parsing: Past, Present, and Future—0
Depression and Anxiety Prediction Using Deep Language Models and Transfer Learning—0
Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak—0
Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation—0
Enhanced Transfer Learning with ImageNet Trained Classification Layer—0
Depth Estimation using Weighted-loss and Transfer Learning—0
DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction—0
Dermoscopic Image Classification with Neural Style Transfer—0
Designing Category-Level Attributes for Discriminative Visual Recognition—0
Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI—0
Deep learning based Hand gesture recognition system and design of a Human-Machine Interface—0
Design Perspectives of Multitask Deep Learning Models and Applications—0
Detail Preserving Residual Feature Pyramid Modules for Optical Flow—0
Detecting and Extracting of Adverse Drug Reaction Mentioning Tweets with Multi-Head Self Attention—0
Detecting Bias in Transfer Learning Approaches for Text Classification—0
Detecting Cadastral Boundary from Satellite Images Using U-Net model—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