Transfer Learning
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Benchmarks
Office-Home
COCO70
Most implemented
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Universal Language Model Fine-tuning for Text Classification
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
High Quality Monocular Depth Estimation via Transfer Learning
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Papers
Multi-Pass, Multi-View Blended Learning for High-Fidelity Volumetric CT Synthesis from Chest X-Rays
Reconstructing volumetric Computed Tomography (CT) from a single 2D chest radiograph (CXR) is an ill-posed inverse problem, further complicated by the scarcity of paired CXR-CT training data. Prior approaches address thi…
Domain AdaptationTransfer LearningGenerative multi-domain transfer learning for fault detection in data-scarce wind turbines
Normal behavior models have shown promise for reliable fault detection in wind turbines. However, these unsupervised anomaly detection models require sufficient fault-free training data to learn the normal operation beha…
Unsupervised Anomaly DetectionTransfer LearningGeneralized Context in Cross Attention for Transfer Learning of Disjoint Tabular Data
Unlike images and text, applying transfer learning to tabular data is challenging due to heterogeneity in feature types, structures, and semantics across disparate domains. Existing methods assume shared features across …
Transfer LearningExplainable Diabetic Retinopathy Classification Using Vision Foundation Models
Diabetic retinopathy (DR) is a major cause of preventable blindness, creating a need for accurate and trustworthy automated screening. This study investigates an explainable DR classification framework using vision found…
Transfer LearningLow-Altitude Fluid Antenna Network with Multi-Agent Reinforcement Learning
Low-altitude wireless networks (LAWNs) integrate terrestrial and aerial platforms to provide ubiquitous communication, sensing, and localization services for unmanned aerial vehicles (UAVs) and electric vertical takeoff …
Multi-agent Reinforcement LearningTransfer LearningSimCast-S2S: An Efficient Generative Model for Subseasonal Precipitation Forecasting via Transfer Learning from Climate Simulations
Subseasonal-to-seasonal (S2S) precipitation forecasting has substantial financial and societal impact, yet remains challenging because of weak predictive signals, high associated uncertainty, and the computational cost o…
Precipitation ForecastingTransfer Learning