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 7676–7700 of 10307 papers

TitleStatusHype
Learn to Talk via Proactive Knowledge Transfer—0
Predicting Helpfulness of Online Reviews—0
Multi-kernel Passive Stochastic Gradient Algorithms and Transfer Learning—0
A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability—0
Few-Shot Learning with Intra-Class Knowledge Transfer—0
Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics—0
Learning to Profile: User Meta-Profile Network for Few-Shot Learning—0
Adaptive multi-channel event segmentation and feature extraction for monitoring health outcomes—0
Physically-Constrained Transfer Learning through Shared Abundance Space for Hyperspectral Image Classification—0
Contact Area Detector using Cross View Projection Consistency for COVID-19 Projects—0
Unsupervised Transfer Learning for Anomaly Detection: Application to Complementary Operating Condition Transfer—0
AlphaNet: Improving Long-Tail Classification By Combining ClassifiersCode0
Siloed Federated Learning for Multi-Centric Histopathology Datasets—0
TopicBERT: A Transformer transfer learning based memory-graph approach for multimodal streaming social media topic detection—0
Unsupervised vs. transfer learning for multimodal one-shot matching of speech and imagesCode0
Hate Speech Detection and Racial Bias Mitigation in Social Media based on BERT model—0
Not 3D Re-ID: a Simple Single Stream 2D Convolution for Robust Video Re-identification—0
Language Models as Few-Shot Learner for Task-Oriented Dialogue Systems—0
Adversarial Knowledge Transfer from Unlabeled DataCode0
Large-scale Transfer Learning for Low-resource Spoken Language Understanding—0
Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task—0
An Efficient Confidence Measure-Based Evaluation Metric for Breast Cancer Screening Using Bayesian Neural NetworksCode0
Facial Expression Recognition Under Partial Occlusion from Virtual Reality Headsets based on Transfer LearningCode0
Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer—0
Transfer Learning Approaches for Streaming End-to-End Speech Recognition System—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