我的长表下部与表格下方的内容重叠。第二个问题是标题没有放在中间。我使用了长表包，表格有 6 页长
\documentclass[journal]{IEEEtran}
\usepackage{graphicx}
% \usepackage{subfigure}
\usepackage{subfig}
\usepackage{caption}
\usepackage{lipsum}
\usepackage{tablefootnote}
\usepackage{hyperref}
\usepackage{amsmath, amssymb}
\usepackage{csquotes}
\usepackage[demo,
export]{adjustbox}
\usepackage{stfloats}
\usepackage{makecell,
ltablex} % new
\keepXColumns
% \raggedbottom
% \usepackage{parskip}
\setcellgapes{3pt}
\usepackage{enumitem}
\usepackage{longtable}
\usepackage{siunitx}
% \usepackage[T1]{fontenc}
% \usepackage[utf8]{inputenc}
\setlength{\LTpre}{0pt}
\setlength{\LTpost}{0pt}
%%
%% \BibTeX command to typeset BibTeX logo in the docs
\setlength\intextsep{\glueexpr\intextsep/2\relax}
\AtBeginDocument{%
\providecommand\BibTeX{{%
\normalfont B\kern-0.5em{\scshape i\kern-0.25em b}\kern-0.8em\TeX}}}
% \maketitle
\begin{document}
\section{ABCD}
Currently, JPEG and JPEG2000 [28] are the international
standards for image compression, and h. 265/HEVC [29]
is the latest video compression standards, which can also
implement the intra-frame coding as image compression.
JPEG is the earliest proposed image compression standard
based on discrete cosine transform (DCT) [30]. After the
image is decomposed by DCT, the high-frequency coefficients are
dramatically quantized and compressed to realize
data compression. However, each coefficient after DCT is
related to all the pixels of the whole image; thus, it requires a
large amount of computation. Therefore, block segmentation
is carried out before implementing the subsequent compression, which leads
to some block artifacts [31] under low bit
rate. Compared with JPEG, JPEG2000 is based on DWT.
Because the length of the base function of the DWT is variable, the
coefficients after DWT only reflect some local features of the input image,
showing good local characteristics.
Currently, JPEG and JPEG2000 [28] are the international
standards for image compression, and h. 265/HEVC [29]
is the latest video compression standards, which can also
implement the intra-frame coding as image compression.
JPEG is the earliest proposed image compression standard
based on discrete cosine transform (DCT) [30]. After the
image is decomposed by DCT, the high-frequency coefficients are dramatically
quantized and compressed to realize
data compression. However, each coefficient after DCT is
related to all the pixels of the whole image; thus, it requires a
large amount of computation. Therefore, block segmentation
is carried out before implementing the subsequent compression, which leads
to some block artifacts [31] under low bit
rate. Compared with JPEG, JPEG2000 is based on DWT.
Because the length of the base function of the DWT is variable, the
coefficients after DWT only reflect some local features of the input
image, showing good local characteristics
\begin{center}
\scriptsize
\onecolumn
\begin{longtable}{|p{1cm}|p{0.5cm}|p{1.5cm}|p{3cm}|p{2cm}|p{8cm}|}
\caption{ABCDDDDDDDDDDDDDDDDDDDDD}\\
\hline
\thead{\textbf{ABCD}}
& \thead{\textbf{ABC}}
& \thead{\textbf{ABCD}}
% & \thead{\specialcell{\textbf{Loss}} \\\
\specialcell{\textbf{Function}}}
& \thead{\specialcell{\textbf{ABCD} \\\ \specialcell{\textbf{ABCD}}} }
& \thead{\specialcell{\textbf{ABCD} \\\ \& \specialcell{\textbf{ABCD}}} }
& \thead{\textbf{ABCD}} \\
% \textbf{First entryFirst entry} & \textbf{Second entryFirst entry} &
\textbf{Third entryFirst entry} & \textbf{Fourth entryFirst entry} \\
\hline
\endfirsthead
\multicolumn{6}{c}%
{\tablename\ \thetable\ -- \textit{Continued from previous page}} \\
\hline
\thead{\textbf{Paper}}
& \thead{\textbf{DNN}}
& \thead{\textbf{Train/Test}}
% & \thead{\specialcell{\textbf{Loss}} \\\
\specialcell{\textbf{Function}}}
& \thead{\specialcell{\textbf{Performance} \\\
\specialcell{\textbf{Measures}}} }
& \thead{\specialcell{\textbf{Complexity} \\\ \&
\specialcell{\textbf{Runtime}}} }
& \thead{\textbf{Critical Findings/Remarks}} \\
% \textbf{First entry} & \textbf{Second entry} & \textbf{Third entry} &
\textbf{Fourth entry} \\
\hline
\endhead
\hline
\multicolumn{6}{r}{\textit{Continued on next page}} \\
\endfoot
\hline
\endlastfoot
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
& \begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\item a
\end{itemize}
\end{minipage} \\
\textbf{vvvv} 2016 & A & a & a &
\begin{minipage}[t]{\linewidth}
\begin{itemize}[topsep=-0.5cm,leftmargin=0.2cm]
\item a
\item a
\end{itemize}
\end{minipage}
\hline
\end{longtable}
\twocolumn
\end{center}
\section{DCBA}
Currently, JPEG and JPEG2000 [28] are the international
standards for image compression, and h. 265/HEVC [29]
is the latest video compression standards, which can also
implement the intra-frame coding as image compression.
JPEG is the earliest proposed image compression standard
based on discrete cosine transform (DCT) [30]. After the
image is decomposed by DCT, the high-frequency coefficients are
dramatically quantized and compressed to realize
data compression. However, each coefficient after DCT is
related to all the pixels of the whole image; thus, it requires a
large amount of computation. Therefore, block segmentation
is carried out before implementing the subsequent compression, which leads
to some block artifacts [31] under low bit
rate. Compared with JPEG, JPEG2000 is based on DWT.
Because the length of the base function of the DWT is variable, the
coefficients after DWT only reflect some local features of the input
image, showing good local characteristics.
Currently, JPEG and JPEG2000 [28] are the international
standards for image compression, and h. 265/HEVC [29]
is the latest video compression standards, which can also
implement the intra-frame coding as image compression.
JPEG is the earliest proposed image compression standard
based on discrete cosine transform (DCT) [30]. After the
image is decomposed by DCT, the high-frequency coefficients are
dramatically quantized and compressed to realize
data compression. However, each coefficient after DCT is
related to all the pixels of the whole image; thus, it requires a
large amount of computation. Therefore, block segmentation
is carried out before implementing the subsequent compression, which leads
to some block artifacts [31] under low bit
rate. Compared with JPEG, JPEG2000 is based on DWT.
Because the length of the base function of the DWT is variable, the
coefficients after DWT only reflect some local features of the input image,
showing good local characteristics.
\end{document}
答案1
你的 MWE 非常不清楚，所以只是一个基于我的答案@leandriis 的评论中提到，您可以执行以下操作：
- 手动将表格拆分为两部分。第一部分必须有
[b]放置选项，第二部分[t]。它们之间不能有任何空格。此操作利用` - 将表格插入到靠近页面开始的位置，以便表格的第一部分在页面上有足够的空间，或者使表格的第一部分足够小以便出现在插入的同一页面上。
- 使用
tabularx表格 - 对于表格内的列表，可以
itemize通过以下方式设置etoolbox：
\usepackage{etoolbox} %
\AtBeginEnvironment{tabularx}{%
\setlist[itemize]{nosep,
leftmargin=*,
label=\textbullet,
before=\begin{minipage}[t]{\linewidth}, % <---
after=\end{minipage} % <---
} }
- 对于规则，使用包中定义的规则
booktabs并删除所有垂直线
您的表格的一个示例（就能够破译表格代码而言）可以是：
\documentclass[journal]{IEEEtran}
%\usepackage{graphicx}
\usepackage{subfig}
\usepackage{caption}
\usepackage{tablefootnote}
\usepackage{amsmath, amssymb}
\usepackage{csquotes}
\usepackage[demo,
export]{adjustbox} % it load graphicx too
\usepackage{stfloats}
\usepackage{booktabs, makecell, tabularx} % changed
\renewcommand\theadfont{\small\bfseries} % new
\renewcommand\theadgape{} % new
\setcellgapes{3pt} % new
\usepackage{siunitx}
\usepackage{enumitem}
\usepackage{etoolbox} %
\AtBeginEnvironment{tabularx}{%
\setlist[itemize]{nosep,
leftmargin=*,
label=\textbullet,
before=\begin{minipage}[t]{\linewidth}, % <---
after=\end{minipage} % <---
} }
\usepackage{hyperref}
\usepackage{lipsum}
\begin{document}
\section{ABCD}
Currently, JPEG and JPEG2000 [28] are the international standards for image compression, and h. 265/HEVC [29] is the latest video compression standards, which can also implement the intra-frame coding as image compression. JPEG is the earliest proposed image compression standard based on discrete cosine transform (DCT) [30]. After the image is decomposed by DCT, the high-frequency coefficients are dramatically quantized and compressed to realize data compression. However, each coefficient after DCT is related to all the pixels of the whole image; thus, it requires a large amount of computation. Therefore, block segmentation is carried out before implementing the subsequent compression, which leads to some block artifacts [31] under low bit rate. Compared with JPEG, JPEG2000 is based on DWT. Because the length of the base function of the DWT is variable, the coefficients after DWT only reflect some local features of the input image, showing good local characteristics.
\begin{table*}[b]
\footnotesize
\setcellgapes{3pt}
\makegapedcells
\caption{ABCDDDDDDDDDDDDDDDDDDDDD}
\begin{tabularx}{\linewidth}{@{} p{1cm} l p{1.5cm} p{3cm} p{2cm} X @{}}
\toprule
\thead{ABCD}
& \thead{ABC}
& \thead{ABCD}
& \thead{Function}
& \thead{ABCD}
& \thead{Critical Findings/Remarks} \\
\midrule
& \multicolumn{3}{c}{\thead{Third entry First entry}}
& \multicolumn{2}{c}{\thead{Fourth entry First entry}} \\
\cmidrule{2-4}\cmidrule(l){5-6}
%%%% table body
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
% \hline
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
% \hline
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\bottomrule
\multicolumn{6}{r}{\textit{Continued on the next page}} \\
\end{tabularx}
\end{table*}
\begin{table*}[t]
\ContinuedFloat
\footnotesize
\setcellgapes{3pt}
\makegapedcells
\caption[]{-- \textit{Continued from previous page}}
\begin{tabularx}{\linewidth}{@{} p{1cm} l p{1.5cm} p{3cm} p{2cm} X @{}}
\toprule
\thead{ABCD}
& \thead{ABC}
& \thead{ABCD}
& \thead{Function}
& \thead{ABCD}
& \thead{Critical Findings/Remarks} \\
\midrule
& \multicolumn{3}{c}{\thead{Third entry First entry}}
& \multicolumn{2}{c}{\thead{Fourth entry First entry}} \\
\cmidrule{2-4}\cmidrule(l){5-6}
%%%% table body
\textbf{vvvv} 2016
& B & C & D & \begin{itemize}
\item a
\item a
\end{itemize}
& \begin{itemize}
\item a
\item a
\item a
\end{itemize} \\
\bottomrule
\end{tabularx}
\end{table*}
% this paragraph are moved after table that the first part of table has enough space page where it is inserted
Currently, JPEG and JPEG2000 [28] are the international standards for image compression, and h. 265/HEVC [29] is the latest video compression standards, which can also implement the intra-frame coding as image compression. JPEG is the earliest proposed image compression standard based on discrete cosine transform (DCT) [30]. After the image is decomposed by DCT, the high-frequency coefficients are dramatically quantized and compressed to realize data compression. However, each coefficient after DCT is related to all the pixels of the whole image; thus, it requires a large amount of computation. Therefore, block segmentation is carried out before implementing the subsequent compression, which leads to some block artifacts [31] under low bit rate. Compared with JPEG, JPEG2000 is based on DWT. Because the length of the base function of the DWT is variable, the coefficients after DWT only reflect some local features of the input image, showing good local characteristics.
\section{DCBA}
Currently, JPEG and JPEG2000 [28] are the international standards for image compression, and h. 265/HEVC [29] is the latest video compression standards, which can also implement the intra-frame coding as image compression. JPEG is the earliest proposed image compression standard based on discrete cosine transform (DCT) [30]. After the image is decomposed by DCT, the high-frequency coefficients are dramatically quantized and compressed to realize data compression. However, each coefficient after DCT is related to all the pixels of the whole image; thus, it requires a large amount of computation. Therefore, block segmentation is carried out before implementing the subsequent compression, which leads to some block artifacts [31] under low bit rate. Compared with JPEG, JPEG2000 is based on DWT. Because the length of the base function of the DWT is variable, the coefficients after DWT only reflect some local features of the input image, showing good local characteristics.
Currently, JPEG and JPEG2000 [28] are the international standards for image compression, and h. 265/HEVC [29] is the latest video compression standards, which can also implement the intra-frame coding as image compression. JPEG is the earliest proposed image compression standard based on discrete cosine transform (DCT) [30]. After the image is decomposed by DCT, the high-frequency coefficients are dramatically quantized and compressed to realize data compression. However, each coefficient after DCT is related to all the pixels of the whole image; thus, it requires a large amount of computation. Therefore, block segmentation is carried out before implementing the subsequent compression, which leads to some block artifacts [31] under low bit rate. Compared with JPEG, JPEG2000 is based on DWT. Because the length of the base function of the DWT is variable, the coefficients after DWT only reflect some local features of the input image, showing good local characteristics.
\end{document}
（红线表示文本区域边框）