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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
1
,
J
an
u
ar
y
20
2
6
:
387
-
3
9
3
388
an
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s
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in
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1
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2.
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ba
s
e
Ou
r
m
o
d
el
was tr
ain
ed
o
n
a
s
e
lectio
n
o
f
th
e
C
OVI
D
-
QU
d
atab
ase
[
1
8
]
.
T
h
is
d
atab
ase
co
n
tain
s
1
,
8
2
3
im
ag
es d
iv
id
ed
in
t
o
th
r
ee
ca
te
g
o
r
ies:
−
C
OVI
D
-
1
9
p
o
s
itiv
e:
5
3
6
im
a
g
es;
n
o
r
m
al:
6
6
8
im
ag
es; lu
n
g
v
ir
u
s
: 6
1
9
i
m
ag
es
Fo
r
o
u
r
s
tu
d
y
,
we
f
o
cu
s
ed
o
n
t
h
e
th
r
ee
ca
teg
o
r
ies
t
h
is
r
ep
r
es
en
ts
a
to
tal
o
f
1
,
8
2
3
im
ag
es.
J
u
s
tific
atio
n
f
o
r
th
e
ch
o
ice
o
f
ca
teg
o
r
ies:
−
C
OVI
D
-
1
9
p
o
s
itiv
e:
a
llo
ws th
e
m
o
d
el
to
lear
n
th
e
d
is
tin
ctiv
e
ch
ar
ac
ter
is
tics
o
f
th
e
d
is
ea
s
e
[
1
9
]
.
−
No
r
m
al:
s
er
v
es a
s
a
r
ef
er
en
ce
f
o
r
co
m
p
ar
is
o
n
a
n
d
d
is
cr
im
in
a
tio
n
.
−
E
x
clu
s
io
n
f
r
o
m
o
th
er
ca
teg
o
r
i
es:
p
u
lm
o
n
ar
y
v
i
r
u
s
:
f
ea
tu
r
es
m
ay
o
v
er
lap
t
h
o
s
e
o
f
C
OVI
D
-
1
9
,
w
h
ich
m
a
y
ca
u
s
e
co
n
f
u
s
io
n
in
th
e
m
o
d
el
[
2
0
]
.
T
h
e
s
ets
of
im
ag
es
in
d
atab
ase
ar
e
d
is
tr
ib
u
ted
:
t
h
e
d
if
f
er
en
ce
b
etwe
en
F
ig
u
r
e
s
1
an
d
2
is
th
at
Fig
u
r
e
1
s
h
o
ws
a
ch
est
af
f
ec
ted
b
y
C
O
VI
D
-
1
9
,
with
g
r
o
u
n
d
-
g
lass
o
p
ac
ities
,
co
n
s
o
lid
atio
n
,
an
d
in
f
i
ltra
tes.
T
h
ese
h
az
y
ar
ea
s
in
th
e
lu
n
g
s
ca
n
ap
p
ea
r
wh
ite
o
n
a
C
XR
[
2
1
]
,
[
2
2
]
,
an
d
ar
e
ca
u
s
ed
b
y
f
l
u
id
b
u
ild
u
p
i
n
th
e
lu
n
g
s
.
T
h
e
d
iag
r
am
i
n
Fig
u
r
e
3
illu
s
tr
ates
th
e
ap
p
r
o
x
im
ate
n
u
m
b
e
r
o
f
p
eo
p
le
af
f
ec
ted
b
y
th
e
C
OVI
D
-
19
p
an
d
em
ic
co
m
p
ar
ed
t
o
th
o
s
e
wh
o
wer
e
n
o
t
in
f
ec
te
d
.
I
t
s
h
o
ws
th
at
th
e
n
u
m
b
er
o
f
a
f
f
ec
te
d
in
d
iv
id
u
als
is
clo
s
e
to
th
at
o
f
th
e
u
n
a
f
f
ec
ted
p
o
p
u
l
atio
n
[
2
3
]
.
Fig
u
r
e
1
.
I
m
ag
es
f
r
o
m
t
h
e
d
ata
s
et
u
s
ed
p
o
s
itiv
e
C
OVI
D
-
19
Fig
u
r
e
2
.
I
m
ag
es
f
r
o
m
th
e
d
ata
s
et
u
s
ed
n
o
r
m
al
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
Dete
ctio
n
o
f COVI
D
-
1
9
u
s
in
g
c
h
est X
-
R
a
ys e
n
h
a
n
ce
d
b
y
h
is
to
g
r
a
m
eq
u
a
liz
a
tio
n
…
(
N
a
z
if Tch
a
g
a
fo
)
389
Fig
u
r
e
3
.
c
o
u
n
t
of
im
ag
es
f
o
r
d
atab
ase
u
s
ed
3
.
2
.
P
r
o
po
s
ed
a
pp
ro
a
ch
T
h
e
s
tu
d
y
was o
r
g
an
ized
i
n
ei
g
h
t m
ain
s
tag
es:
−
I
m
ag
e
s
ize
s
tan
d
ar
d
izatio
n
:
a
l
l
i
m
a
ges
h
ave
b
ee
n
r
es
i
ze
d
t
o
a
uni
f
or
m
s
i
ze
t
o
en
sur
e
cons
i
st
enc
y
in
l
ea
r
ni
n
g.
(
)
=
(
=
)
=
,
0
≤
<
(
1
)
x
k
:
d
is
cr
ete
in
ten
s
ity
lev
el
(
g
r
a
y
lev
el
)
;
L
:
to
tal
n
u
m
b
e
r
o
f
p
o
s
s
ib
le
in
ten
s
ity
lev
els
n
k
:
ab
s
o
lu
te
f
r
e
q
u
en
c
y
(
p
ix
el
c
o
u
n
t
)
a
n
d
n
is
to
tal
n
u
m
b
e
r
o
f
p
ix
els in
th
e
im
ag
e
p
x
(
x
k
)
:
p
r
o
b
a
b
ilit
y
m
ass
f
u
n
ctio
n
(
PMF)
o
r
n
o
r
m
alize
d
f
r
eq
u
e
n
cy
−
C
o
n
v
er
t
im
ag
es
to
g
r
ay
s
ca
le
T
h
e
g
r
ay
s
ca
le
co
n
v
er
s
io
n
allo
wed
f
o
c
u
s
o
n
tex
tu
r
e
a
n
d
b
r
ig
h
tn
ess
in
f
o
r
m
atio
n
,
wh
ile
r
e
d
u
cin
g
d
ata
co
m
p
lex
ity
with
f
u
n
ctio
n
g
r
ay
s
ca
le
in
p
y
th
o
n
[
2
4
]
.
B
r
ea
k
d
o
wn
o
f
d
ata
in
to
lear
n
in
g
an
d
v
alid
atio
n
s
ets:
8
0
%
o
f
th
e
d
ata
wer
e
u
s
ed
f
o
r
m
o
d
el
lear
n
in
g
(
lear
n
in
g
s
et)
.
2
0
%
o
f
th
e
d
ata
wer
e
u
s
ed
to
ass
ess
th
e
r
eliab
ilit
y
o
f
th
e
m
o
d
el
(
v
alid
atio
n
s
et)
[
2
5
]
,
[
2
6
]
.
−
Desig
n
of
th
e
C
NN
ar
ch
itectu
r
e
T
h
e
C
NN
ar
ch
itectu
r
e
was
d
ef
in
ed
by
s
p
ec
if
y
in
g
th
e
n
u
m
b
er
an
d
ty
p
e
of
co
n
v
o
lu
tio
n
al
an
d
f
u
lly
co
n
n
ec
ted
lay
er
s
[
2
7
]
.
T
h
e
C
NN
ar
ch
itectu
r
e
p
lay
s
a
cr
u
cia
l
r
o
le
in
its
ab
ilit
y
to
ef
f
ec
tiv
ely
d
etec
t
C
OVI
D
-
1
9
f
r
o
m
C
XR
s
[
2
8
]
,
[
2
9
]
.
T
h
is
ar
ch
itectu
r
e
Fig
u
r
e
4
is
d
ef
in
ed
b
y
s
p
ec
if
y
in
g
s
ev
er
al
k
ey
ele
m
en
ts
:
n
u
m
b
er
an
d
ty
p
e
o
f
c
o
n
v
o
lu
tio
n
al
lay
e
r
s
an
d
f
u
lly
co
n
n
ec
ted
lay
er
s
[
3
0
]
.
Fig
u
r
e
4
.
Ar
c
h
itectu
r
e
C
NN
u
s
ed
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
1
,
J
an
u
ar
y
20
2
6
:
387
-
3
9
3
390
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
Mo
d
el
d
r
iv
e
s
etu
p
,
t
h
e
h
y
p
e
r
p
ar
am
eter
s
o
f
th
e
m
o
d
el,
s
u
ch
as
th
e
lear
n
i
n
g
r
at
e
a
n
d
th
e
n
u
m
b
e
r
of
er
as,
h
av
e
b
ee
n
o
p
tim
ized
to
o
b
tain
th
e
b
est
r
esu
lts
[
3
0
]
.
W
h
ile
d
ef
in
in
g
t
h
e
C
NN
ar
ch
itectu
r
e
is
ess
en
tial,
ac
h
iev
in
g
o
p
tim
al
p
er
f
o
r
m
an
ce
o
f
ten
r
e
q
u
ir
es
f
in
e
-
tu
n
in
g
th
e
m
o
d
el
’
s
h
y
p
e
r
p
ar
am
ete
r
s
[
3
1
]
.
T
h
ese
ar
e
s
ettin
g
s
th
at
co
n
tr
o
l th
e
lear
n
in
g
p
r
o
ce
s
s
b
u
t a
r
en
’
t d
ir
ec
tly
l
ea
r
n
ed
b
y
th
e
m
o
d
el
its
elf
[
3
2
]
.
Mo
d
el
tr
ain
in
g
lau
n
c
h
,
t
h
e
m
o
d
e
l
was
tr
ain
ed
o
n
th
e
lear
n
in
g
s
et
an
d
its
p
er
f
o
r
m
a
n
ce
was
ev
alu
ated
o
n
th
e
v
alid
atio
n
s
et
[
3
3
]
.
B
y
f
o
llo
win
g
th
ese
s
tep
s
,
we
wer
e
ab
le
to
d
ev
el
o
p
a
C
NN
m
o
d
el
ca
p
ab
le
o
f
d
etec
tin
g
C
OVI
D
-
1
9
f
r
o
m
C
XR
s
with
h
ig
h
ac
cu
r
ac
y
an
d
r
eliab
ilit
y
[
3
4
]
.
Op
tim
izin
g
th
e
s
e
h
y
p
er
p
ar
am
ete
r
s
ca
n
s
ig
n
if
ican
tly
im
p
r
o
v
e
th
e
m
o
d
el
’
s
ab
ilit
y
to
d
etec
t
C
OVI
D
-
1
9
in
C
XR
s
[
3
5
]
.
I
n
Fig
u
r
e
5
wh
ich
s
h
o
w
th
e
g
r
ap
h
o
r
ac
c
u
r
ac
y
a
n
d
Fig
u
r
e
6
wh
ich
s
h
o
w
e
v
o
lu
tio
n
o
f
lo
s
s
v
alu
e
[
3
6
]
.
Fig
u
r
e
5
.
Acc
u
r
ac
y
v
alu
e
Fig
u
r
e
6
.
L
o
s
s
v
alu
e
L
ast
p
h
ase
o
f
th
e
s
tu
d
y
,
u
p
o
n
th
e
c
o
m
p
letio
n
o
f
th
e
C
NN
tr
ain
in
g
p
h
ase,
two
s
u
b
s
eq
u
en
t
cr
itical
s
tep
s
ar
e
u
n
d
er
tak
en
to
r
ig
o
r
o
u
s
ly
q
u
an
tify
an
d
v
alid
ate
th
e
m
o
d
el
’
s
p
r
e
d
ictiv
e
p
er
f
o
r
m
an
ce
o
n
th
e
u
n
s
ee
n
test
d
ata:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
Dete
ctio
n
o
f COVI
D
-
1
9
u
s
in
g
c
h
est X
-
R
a
ys e
n
h
a
n
ce
d
b
y
h
is
to
g
r
a
m
eq
u
a
liz
a
tio
n
…
(
N
a
z
if Tch
a
g
a
fo
)
391
4
.
1
.
Vis
ua
lize
t
he
co
nfusi
o
n
m
a
t
rix
T
h
e
co
n
f
u
s
io
n
m
atr
ix
s
er
v
es
as
an
ess
en
tial
d
iag
n
o
s
tic
t
o
o
l
f
o
r
v
is
u
alizin
g
a
m
o
d
el
’
s
p
r
ed
ictiv
e
ac
cu
r
ac
y
b
y
m
ap
p
in
g
f
o
r
ec
ast
ed
o
u
tco
m
es
ag
ain
s
t
ac
tu
al
g
r
o
u
n
d
tr
u
th
v
alu
es.
T
h
is
s
tr
u
ctu
r
ed
r
ep
r
esen
tatio
n
f
ac
ilit
ates
a
co
m
p
r
eh
en
s
iv
e
ev
alu
atio
n
o
f
p
e
r
f
o
r
m
an
ce
,
as
it
h
ig
h
lig
h
ts
s
p
ec
if
ic
p
att
er
n
s
o
f
s
u
cc
ess
f
u
l
class
if
icatio
n
s
an
d
s
y
s
tem
at
i
c
er
r
o
r
s
ac
r
o
s
s
d
if
f
er
en
t
ca
teg
o
r
ies
[
3
6
]
.
Fu
r
t
h
er
m
o
r
e,
b
y
is
o
latin
g
th
ese
p
r
ed
ictiv
e
d
is
cr
ep
a
n
cies,
r
esear
ch
er
s
ca
n
d
er
iv
e
cr
itical
s
ec
o
n
d
ar
y
m
etr
ics
s
u
ch
as
p
r
ec
is
io
n
,
r
ec
all,
an
d
th
e
F1
-
s
co
r
e
to
g
ain
d
ee
p
er
in
s
ig
h
ts
in
to
th
e
alg
o
r
ith
m
’
s
r
eliab
ilit
y
in
co
m
p
le
x
d
ec
is
io
n
-
m
ak
in
g
s
ce
n
ar
io
s
.
4
.
2
.
Dis
pla
y
t
he
re
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ated
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u
r
e
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ip
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[
3
6
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.
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u
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ates
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F
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Au
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ax
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ip
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
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52
In
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[
1
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Z.
X
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a
l
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,
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2
]
Q
.
L
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t
a
l
.
,
“
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t
r
a
n
smis
si
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.
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.
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ma
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,
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.
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