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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8801–8850 of 10307 papers

TitleStatusHype
Convolutional Neural Networks for Histopathology Image Classification: Training vs. Using Pre-Trained Networks—0
Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay—0
Convolutional Neural Networks for Classifying Melanoma Images—0
Convolutional Neural Networks for Financial Text Regression—0
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?—0
Convolutional Neural Networks for the classification of glitches in gravitational-wave data streams—0
Convolutional Neural Networks Towards Facial Skin Lesions Detection—0
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment—0
Cooperative Self-training of Machine Reading Comprehension—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—0
COPD Classification in CT Images Using a 3D Convolutional Neural Network—0
CopyPaste: An Augmentation Method for Speech Emotion Recognition—0
CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise—0
Coregionalised Locomotion Envelopes - A Qualitative Approach—0
Core Sampling Framework for Pixel Classification—0
Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique—0
COSTA: Co-Occurrence Statistics for Zero-Shot Classification—0
Cost-based Feature Transfer for Vehicle Occupant Classification—0
Cost-effective Variational Active Entity Resolution—0
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation—0
COT: Unsupervised Domain Adaptation With Clustering and Optimal Transport—0
Could Giant Pretrained Image Models Extract Universal Representations?—0
Count, Decode and Fetch: A New Approach to Handwritten Chinese Character Error Correction—0
Counterfactual Thinking for Long-tailed Information Extraction—0
Coupled End-to-End Transfer Learning With Generalized Fisher Information—0
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation—0
Covariance-Generalized Matching Component Analysis for Data Fusion and Transfer Learning—0
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks—0
COVID-19: Comparative Analysis of Methods for Identifying Articles Related to Therapeutics and Vaccines without Using Labeled Data—0
COVID-19 Detection and Analysis From Lung CT Images using Novel Channel Boosted CNNs—0
COVID-19 Detection Based on Self-Supervised Transfer Learning Using Chest X-Ray Images—0
Covid-19 Detection from Chest X-ray and Patient Metadata using Graph Convolutional Neural Networks—0
COVID-19 Detection Using Slices Processing Techniques and a Modified Xception Classifier from Computed Tomography Images—0
COVID-19 Detection using Transfer Learning with Convolutional Neural Network—0
COVID 19 Diagnosis Analysis using Transfer Learning—0
COVID-19 Infection Analysis Framework using Novel Boosted CNNs and Radiological Images—0
COVID-19 therapy target discovery with context-aware literature mining—0
CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis—0
COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19—0
COVID_MTNet: COVID-19 Detection with Multi-Task Deep Learning Approaches—0
COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images—0
C-Procgen: Empowering Procgen with Controllable Contexts—0
Crack Detection in Infrastructure Using Transfer Learning, Spatial Attention, and Genetic Algorithm Optimization—0
Crackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolitional Neural Networks—0
Crack-Net: Prediction of Crack Propagation in Composites—0
Cramnet: Layer-wise Deep Neural Network Compression with Knowledge Transfer from a Teacher Network—0
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks—0
Creation of Novel Soft Robot Designs using Generative AI—0
Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending—0
Critical Assessment of Transfer Learning for Medical Image Segmentation with Fully Convolutional Neural Networks—0
Show:102550
← PrevPage 177 of 207Next →
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