摘要在人工智能迅速发展的今天, 深度神经网络广泛应用于各个研究领域并取得了巨大的成功,
但也同样面临着诸多挑战. 首先, 为了解决复杂的问题和提高模型的训练效果 …

Despite the success of deep neural networks (DNNs) in almost every field, their deployment
on edge devices has been restricted due to the significant memory and computational …

Abstract Knowledge distillation (KD) and model averaging (MA) are prominent techniques
for enhancing the efficiency and effectiveness of deep neural networks (DNNs). MA …

Knowledge Distillation (KD) enhances the generalization ability of a student model by
transferring knowledge from a teacher model. However, literature suggests that the student …

The unprecedented success of deep neural networks (DNNs), especially convolutional
neural networks (CNNs), stems from its high representational power and capability to model …