The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …

The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …

Abstract Vision Transformers (ViT) have shown rapid progress in computer vision tasks,
achieving promising results on various benchmarks. However, due to the massive number of …

Convolutional neural network (CNN) pruning has become one of the most successful
network compression approaches in recent years. Existing works on network pruning …

Deep Neural Networks (DNNs) are becoming an important tool in modern computing
applications. Accelerating their training is a major challenge and techniques range from …

摘要近年来, 卷积神经网络(Convolutional neural network, CNNs) 在计算机视觉,
自然语言处理, 语音识别等领域取得了突飞猛进的发展, 其强大的特征学习能力引起了国内外 …

Abstract Recent efforts in Neural Rendering Fields (NeRF) have shown impressive results
on novel view synthesis by utilizing implicit neural representation to represent 3D scenes …

In recent years, it has been witnessed that the systolic array is a successful architecture for
DNN hardware accelerators. However, the design of systolic arrays also encountered many …

Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …

Leveraging sparsity in deep neural network (DNN) models is promising for accelerating
model inference. Yet existing GPUs can only leverage the sparsity from weights but not …