Abstract: In real-world scenarios, the number of training samples across classes usually subjects to a long-tailed distribution. The conventionally trained network may achieve unexpected inferior ...

Abstract: Convolutional neural networks are fundamental to deep learning, especially in computer vision. However, their computational demands, particularly during batch normalization, create ...

Batch normalization (BatchNorm) is a widely adopted technique that enables faster and more stable training of deep neural networks. However, despite its pervasiveness, the exact reasons for ...

What is Batch Normalization? Training a neural network is performed according to the high-level supervised machine learning process. A batch of data is fed through the model, after which its ...