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 2151–2175 of 10307 papers

TitleStatusHype
Advancing Efficient Brain Tumor Multi-Class Classification -- New Insights from the Vision Mamba Model in Transfer Learning—0
DARTS: Dialectal Arabic Transcription System—0
Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican—0
Data augmentation with mixtures of max-entropy transformations for filling-level classification—0
Data-Efficient Challenges in Visual Inductive Priors: A Retrospective—0
DATSING: Data Augmented Time Series Forecasting with Adversarial Domain Adaptation—0
Detection of Myocardial Infarction Based on Novel Deep Transfer Learning Methods for Urban Healthcare in Smart Cities—0
Canoe : A System for Collaborative Learning for Neural Nets—0
Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World—0
Can Multisensory Cues in VR Help Train Pattern Recognition to Citizen Scientists?—0
A Novel Deep Learning Method for Textual Sentiment Analysis—0
Advancing Diagnostic Precision: Leveraging Machine Learning Techniques for Accurate Detection of Covid-19, Pneumonia, and Tuberculosis in Chest X-Ray Images—0
SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models—0
Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?—0
Can Machine Translation Bridge Multilingual Pretraining and Cross-lingual Transfer Learning?—0
A novel database of Children's Spontaneous Facial Expressions (LIRIS-CSE)—0
A Novel Channel Boosted Residual CNN-Transformer with Regional-Boundary Learning for Breast Cancer Detection—0
A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling—0
Can LLMs Grade Short-Answer Reading Comprehension Questions : An Empirical Study with a Novel Dataset—0
Cancer Registry Information Extraction via Transfer Learning—0
A novel approach towards the classification of Bone Fracture from Musculoskeletal Radiography images using Attention Based Transfer Learning—0
Improving Cancer Hallmark Classification with BERT-based Deep Learning Approach—0
Can bidirectional encoder become the ultimate winner for downstream applications of foundation models?—0
An Intensity and Phase Stacked Analysis of Phase-OTDR System using Deep Transfer Learning and Recurrent Neural Networks—0
Advancing Automated Knowledge Transfer in Evolutionary Multitasking via Large Language Models—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