A 34-fps 698-GOP/s/W binarized deep neural network-based natural scene text interpretation accelerator for mobile edge computing

• Main Authors: Li, Yixing, Liu, Zichuan, Liu, Wenye, Jiang, Yu, Wang, Yongliang, Goh, Wang Ling, Yu, Hao, Ren, Fengbo
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Application Specific Integrated Circuits; Mobile Applications
• Online Access: https://hdl.handle.net/10356/150987
• Institution: Nanyang Technological University

The scene text interpretation is a critical part of the natural scene interpretation. Currently, most of the existing work is based on high-end graphics processing units (GPUs) implementation, which is commonly used on the server side. However, in Internet of Things (IoT) application scenarios, the...