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 3201–3250 of 10307 papers

TitleStatusHype
DoQA -- Accessing Domain-Specific FAQs via Conversational QA—0
DoQA - Accessing Domain-Specific FAQs via Conversational QA—0
Dose Prediction with Deep Learning for Prostate Cancer Radiation Therapy: Model Adaptation to Different Treatment Planning Practices—0
Do sound event representations generalize to other audio tasks? A case study in audio transfer learning—0
Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup—0
Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization—0
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks—0
DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Reconstruction and Rendering—0
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain—0
Double Transfer Learning for Breast Cancer Histopathologic Image Classification—0
Deep Learning-based Bio-Medical Image Segmentation using UNet Architecture and Transfer Learning—0
Deep Learning based Automated Forest Health Diagnosis from Aerial Images—0
Do We Really Need a Large Number of Visual Prompts?—0
DRAFT: A Novel Framework to Reduce Domain Shifting in Self-supervised Learning and Its Application to Children's ASR—0
Automatic Speech Recognition for Sanskrit with Transfer Learning—0
DRDr: Automatic Masking of Exudates and Microaneurysms Caused By Diabetic Retinopathy Using Mask R-CNN and Transfer Learning—0
Deep Learning-based Anomaly Detection on X-ray Images of Fuel Cell Electrodes—0
DRDrV3: Complete Lesion Detection in Fundus Images Using Mask R-CNN, Transfer Learning, and LSTM—0
DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer—0
Automatic Sleep Stage Classification with Cross-modal Self-supervised Features from Deep Brain Signals—0
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments—0
DRG-Net: Interactive Joint Learning of Multi-lesion Segmentation and Classification for Diabetic Retinopathy Grading—0
A Comparison of Methods for Neural Network Aggregation—0
Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency—0
Driving Tasks Transfer in Deep Reinforcement Learning for Decision-making of Autonomous Vehicles—0
Dropping Networks for Transfer Learning—0
Drowsiness Detection Based On Driver Temporal Behavior Using a New Developed Dataset—0
DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models—0
Automatic segmentation of texts into units of meaning for reading assistance—0
Drug repositioning for Alzheimer's disease with transfer learning—0
Energy efficient distributed analytics at the edge of the network for IoT environments—0
DS4DH at TREC Health Misinformation 2021: Multi-Dimensional Ranking Models with Transfer Learning and Rank Fusion—0
Building and Road Segmentation Using EffUNet and Transfer Learning Approach—0
Novel coronavirus pneumonia lesion segmentation in CT images—0
Analysis and Prediction of NLP models via Task Embeddings—0
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning—0
DT-LET: Deep Transfer Learning by Exploring where to Transfer—0
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach—0
Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors—0
DuA: Dual Attentive Transformer in Long-Term Continuous EEG Emotion Analysis—0
Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning—0
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis—0
Dual Branch Deep Learning Network for Detection and Stage Grading of Diabetic Retinopathy—0
Dual-Correction Adaptation Network for Noisy Knowledge Transfer—0
Dual Decomposition of Weights and Singular Value Low Rank Adaptation—0
Automatic Recognition of the Supraspinatus Tendinopathy from Ultrasound Images using Convolutional Neural Networks—0
Dual Memory Architectures for Fast Deep Learning of Stream Data via an Online-Incremental-Transfer Strategy—0
Dual Path Structural Contrastive Embeddings for Learning Novel Objects—0
Analysis and Adaptation of YOLOv4 for Object Detection in Aerial Images—0
Deep Learning Approach Combining Lightweight CNN Architecture with Transfer Learning: An Automatic Approach for the Detection and Recognition of Bangladeshi Banknotes—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