From 915af0c8ee4d7a51ad51efca37b49c68b1c7d3ed Mon Sep 17 00:00:00 2001 From: Hobe Date: Mon, 8 Jun 2020 04:57:16 +0000 Subject: [PATCH] fix typo. git-svn-id: http://newslabx.csie.ntu.edu.tw/svn/Ginger@77 5747cdd2-2146-426f-b2b0-0570f90b98ed --- trunk/RTCSA_SS/02Background.tex | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/trunk/RTCSA_SS/02Background.tex b/trunk/RTCSA_SS/02Background.tex index e71958b..1e99cfe 100644 --- a/trunk/RTCSA_SS/02Background.tex +++ b/trunk/RTCSA_SS/02Background.tex @@ -11,7 +11,7 @@ C. Dong et al.~\cite{ChaoDong16} proposed a deep learning method for single imag super-resolution (SR). Their method learns how to directly map the low-resolution image to high-resolution image. They show that the traditional sparse coding based SR methods can be reformulated into a deep convolutional neural network. -SRCNN consists three operations.%, illustrated in Figure~\ref{fig:SRCNN_model}. +SRCNN consists three operations. The first layer of SRCNN model extracts the patches from low-resolution image. The second layer maps the patches from low-resolution to high-resolution. The third layer will reconstruct the high-resolution image by the high-resolution @@ -27,7 +27,7 @@ patches. \subsection{Thermal cameras} In this work, we use two different resolution thermal cameras to play the role -of low-resolution and high-resolution camera. For low-resolution camera, we use +of low-resolution and high-resolution cameras. For low-resolution camera, we use Grid-EYE thermal camera. Grid-EYE is a thermal camera that can output $8 \times 8$ pixels thermal data with $2.5^\circ C$ accuracy and $0.25^\circ C$ resolution at $10$ fps. For the high-resolution one, we use Lepton 3. The