3 Result(s)
-
Chapter and Conference Paper
A CNN-Based Multi-scale Super-Resolution Architecture on FPGA for 4K/8K UHD Applications
In this paper, based on our previous work, we present a multi-scale super-resolution (SR) hardware (HW) architecture using a convolutional neural network (CNN), where the up-scaling factors of 2, 3 and 4 are s...
-
Chapter and Conference Paper
Single Image Super-Resolution Using Lightweight CNN with Maxout Units
Rectified linear units (ReLU) are well-known to obtain higher performance for deep-learning-based applications. However, networks with ReLU tend to perform poorly when the number of parameters is constrained. ...
-
Chapter and Conference Paper
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tracks. In the first one, partic...
