67‐1: Distinguished Paper: Efficient Multi‐Quality Super Resolution Using a Deep Convolutional Neural Network for an FPGA Implementation. Issue 1 (25th September 2020)

• Record Type: Journal Article
• Authors: Kim, Min Beom; Lee, Sanglyn; Kim, Ilho; Hong, Hee Jung; Kim, Chang Gone; Yoon, Soo Young
• Is Part Of: Digest of technical papers. Volume 51:Issue 1(2020)
• Page Start: 993
• Page End: 996
• Publication Date: 2020-09-25
• Subjects: Deep-learning -- Super-resolution; Information display systems -- Congresses; 621.3815422
• DOI: 10.1002/sdtp.14039
• Languages: English
• ISSNs: 0097-966X

Abstract

Abstract : We propose an efficient deep convolutional neural network for a super‐resolution which is capable of multiple‐quality input, by analyzing the input quality and choosing appropriate features automatically. To implement the network in an FPGA and an ASIC, we employ a network trimming technique to compress the neural network.