T Choudhary, V Mishra, A Goswami… - Artificial Intelligence …, 2020 - Springer
In recent years, machine learning (ML) and deep learning (DL) have shown remarkable improvement in computer vision, natural language processing, stock prediction, forecasting …
Light-weight convolutional neural networks (CNNs) are specially designed for applications on mobile devices with faster inference speed. The convolutional operation can only capture …
Despite the fact that deep neural networks are powerful models and achieve appealing results on many tasks, they are too large to be deployed on edge devices like smartphones …
Y He, P Liu, Z Wang, Z Hu… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Previous works utilized" smaller-norm-less-important" criterion to prune filters with smaller norm values in a convolutional neural network. In this paper, we analyze this norm-based …
This paper proposed a Soft Filter Pruning (SFP) method to accelerate the inference procedure of deep Convolutional Neural Networks (CNNs). Specifically, the proposed SFP …
Currently, with the rapid development of deep learning, deep neural networks (DNNs) have been widely applied in various computer vision tasks. However, in the pursuit of …
T Wang, L Yuan, X Zhang… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
State-of-the-art CNN based recognition models are often computationally prohibitive to deploy on low-end devices. A promising high level approach tackling this limitation is …
Y Cheng, D Wang, P Zhou… - IEEE Signal Processing …, 2018 - ieeexplore.ieee.org
In recent years, deep neural networks (DNNs) have received increased attention, have been applied to different applications, and achieved dramatic accuracy improvements in many …