SIFT-Aided-Rectified-2D-DIC-for-Accurate-Asphalt-Concrete-Testing-Measurements

Adaptive-Testing-Environment-Generation-for-Connected-and-Automated-Vehicles-with-Dense-Reinforcement-Learning

WanJuan-CC-A-Safe-and-High-Quality-Open-sourced-English-Webtext-Dataset-Derived-from-Common-Crawl-Data

Mobile-Health-Text-Misinformation-Identification-Using-Mobile-Data-Mining

Estimation-and-Deconvolution-of-Second-Order-Cyclostationary-Signals

Fundamental-Limits-of-Throughput-and-Availability-in-Resource-Allocation

Degradation-Modeling-and-Prognostic-Analysis-Under-Unknown-Failure-Modes

StiefelGen-Time-Series-Data-Augmentation-Approach


In this work, the authors propose Unified Batch Normalization (UBN) to address feature condensation in Batch Normalization (BN). By introducing a two-stage framework, UBN significantly enhances performance and training efficiency by rectifying normalization components and mitigating feature condensation.


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unified-batch-normalization-addressing-feature-condensation-in-neural-networks


Unified Batch Normalization: Addressing Feature Condensation in Neural Networks


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Neural Network Techniques