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v
e
ac
tio
n
ca
n
b
e
ta
k
e
n
i
n
o
r
d
er
to
tac
k
le
t
h
e
p
r
o
b
le
m
ar
is
e
[
5
]
.
Dis
ea
s
e
m
a
n
ag
e
m
e
n
t
i
s
a
ch
alle
n
g
i
n
g
tas
k
.
Mo
s
tl
y
d
is
ea
s
e
s
ar
e
s
ee
n
o
n
th
e
leav
es
o
r
s
te
m
s
o
f
th
e
p
lan
t.
P
r
ec
is
e
q
u
an
tif
ica
tio
n
o
f
th
e
s
e
v
is
u
a
ll
y
o
b
s
er
v
ed
d
is
ea
s
es,
p
est
s
,
tr
aits
h
av
e
n
o
t
s
tu
d
ied
y
e
t
b
ec
au
s
e
o
f
th
e
o
m
p
lex
i
t
y
o
f
v
i
s
u
al
p
atter
n
s
.
H
en
ce
ter
e
h
a
s
b
ee
n
in
cr
ea
s
i
n
g
d
e
m
an
d
f
o
r
m
o
r
e
s
p
ec
if
ic
an
d
s
o
p
h
i
s
ticated
i
m
ag
e
p
atter
n
u
n
d
er
s
ta
n
d
i
n
g
[
6
]
.
T
h
e
ap
p
licatio
n
o
f
i
m
a
g
e
p
r
o
ce
s
s
i
n
g
an
d
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM)
cla
s
s
i
f
ier
a
lg
o
r
it
h
m
ca
n
b
e
d
o
n
e
b
y
u
s
i
n
g
M
A
T
L
A
B
s
o
f
t
w
ar
e
a
s
t
h
e
p
lat
f
o
r
m
.
M
A
T
L
A
B
i
s
t
h
e
s
h
o
r
t
f
o
r
m
o
f
Ma
tr
i
x
L
ab
o
r
ato
r
y
as
i
ts
b
asic
d
ata
ele
m
en
t
i
s
th
e
m
a
tr
ix
.
A
s
i
m
p
le
in
te
g
er
is
co
n
s
id
er
ed
as
m
a
tr
ix
o
f
o
n
e
r
o
w
a
n
d
o
n
e
co
lu
m
n
.
Sev
er
al
m
a
th
e
m
atica
l
o
p
er
atio
n
s
th
at
w
o
r
k
o
n
ar
r
a
y
s
o
r
m
atr
ices
ar
e
b
u
ilt
-
i
n
to
th
e
M
AT
L
A
B
en
v
ir
o
n
m
en
t.
MA
T
L
A
B
w
a
s
c
h
o
s
en
b
ec
au
s
e
it is
a
co
m
p
u
ti
n
g
p
latf
o
r
m
t
h
at
is
ca
p
ab
le
o
f
d
ev
elo
p
in
g
a
n
d
test
i
n
g
n
u
m
b
er
o
f
ap
p
licatio
n
s
in
i
t.
T
h
e
m
aj
o
r
ad
v
an
ta
g
e
o
f
u
s
i
n
g
M
A
T
L
A
B
s
o
f
t
w
ar
e
co
m
p
ar
ed
to
o
t
h
er
s
o
f
t
w
ar
e
i
s
th
e
g
r
ap
h
ical
u
s
er
in
ter
f
ac
e
(
GUI
)
w
h
ic
h
ca
n
co
n
tr
ib
u
te
p
o
s
iti
v
el
y
to
u
n
d
er
s
ta
n
d
t
h
e
co
n
ce
p
ts
w
it
h
ea
s
e.
T
h
e
p
icto
r
ial
illu
s
tr
atio
n
s
co
n
f
er
b
etter
u
n
d
er
s
ta
n
d
in
g
o
f
t
h
e
co
n
ce
p
ts
w
i
th
ea
s
e
[
7
]
.
T
h
e
p
r
o
ce
s
s
o
f
p
r
o
ce
s
s
i
n
g
d
i
g
ital
i
m
a
g
es
w
it
h
v
ar
io
u
s
tec
h
n
iq
u
es
is
k
n
o
w
n
as
s
u
ch
as
d
ig
ital
i
m
a
g
e
p
r
o
ce
s
s
in
g
.
T
h
e
p
r
o
c
ess
i
n
cl
u
d
es
i
m
ag
e
r
esto
r
atio
n
,
i
m
a
g
e
de
-
n
o
is
i
n
g
,
i
m
ag
e
s
e
g
m
en
ta
t
io
n
,
an
d
also
ed
g
e
d
etec
tio
n
o
f
th
e
i
m
ag
e.
I
n
t
h
is
m
o
d
er
n
er
a
,
th
e
d
ig
ital
i
m
a
g
e
p
r
o
ce
s
s
i
n
g
p
la
y
s
a
n
im
p
o
r
ta
n
t
p
ar
t
in
a
tech
n
o
lo
g
y
d
ev
elo
p
m
en
t
i
n
cl
u
d
in
g
all
s
ec
to
r
s
[
8
]
.
A
s
t
h
e
class
i
f
ier
,
t
h
e
SVM
w
as
c
h
o
s
e
n
to
b
e
u
s
ed
b
ec
au
s
e
s
u
p
p
o
r
t
v
ec
to
r
lear
n
in
g
is
b
ased
o
n
s
i
m
p
le
id
ea
s
w
h
ic
h
h
av
e
its
o
r
ig
i
n
in
s
tat
is
tical
le
ar
n
in
g
th
eo
r
y
.
T
h
e
s
i
m
p
lic
it
y
co
m
e
s
f
r
o
m
th
e
f
ac
t
th
a
t
S
VM
ap
p
l
y
a
s
i
m
p
le
li
n
ea
r
m
et
h
o
d
to
t
h
e
d
ata
b
u
t
in
a
h
i
g
h
-
d
i
m
e
n
s
io
n
al
f
ea
t
u
r
e
s
p
ac
e
n
o
n
-
li
n
ea
r
l
y
r
el
ated
to
th
e
in
p
u
t
s
p
ac
e.
Mo
r
eo
v
er
,
ev
en
t
h
o
u
g
h
w
e
ca
n
t
h
in
k
o
f
S
VM
s
as
a
lin
ea
r
alg
o
r
it
h
m
in
a
h
ig
h
-
d
i
m
en
s
io
n
a
l
s
p
ac
e,
in
p
r
ac
tice,
it
d
o
es
n
o
t
in
v
o
l
v
e
an
y
co
m
p
u
tatio
n
s
i
n
th
at
h
i
g
h
d
i
m
en
s
io
n
al
s
p
ac
e.
T
h
is
s
i
m
p
licit
y
co
m
b
in
ed
w
it
h
s
tate
o
f
th
e
ar
t
p
er
f
o
r
m
a
n
ce
o
n
m
a
n
y
lear
n
in
g
p
r
o
b
le
m
s
s
u
c
h
as
clas
s
if
icatio
n
,
r
e
g
r
ess
io
n
,
a
n
d
n
o
v
elt
y
d
etec
ti
o
n
h
a
s
co
n
tr
ib
u
ted
to
th
e
p
o
p
u
lar
it
y
o
f
th
e
SVM
[
9
]
,
[
1
0
]
.
L
ea
f
d
i
s
ea
s
e
d
etec
tio
n
i
m
ag
e
p
r
o
ce
s
s
in
g
t
h
at
ca
n
r
ec
o
g
n
ize
p
r
o
b
le
m
s
i
n
cr
o
p
s
f
r
o
m
i
m
a
g
e
s
,
b
ased
o
n
co
lo
u
r
,
tex
tu
r
e
a
n
d
s
h
ap
e
to
au
to
m
a
ticall
y
d
etec
t
d
is
ea
s
es
a
n
d
g
iv
e
t
h
e
f
ast
a
n
d
a
cc
u
r
ate
s
o
lu
tio
n
s
to
th
e
f
ar
m
er
w
as s
tu
d
ied
b
y
[
1
1
]
w
h
ic
h
co
n
ce
n
tr
ated
o
n
t
h
e
af
f
ec
ted
ar
ea
o
f
d
is
ea
s
es a
n
d
clas
s
if
ica
tio
n
.
T
h
e
cu
r
r
en
t
m
et
h
o
d
n
o
w
w
as
s
aid
to
co
n
s
u
m
e
m
o
r
e
ti
m
e
is
b
ec
au
s
e
h
u
m
an
ca
n
ca
u
s
e
er
r
o
r
,
an
d
th
is
ca
n
lead
to
co
n
s
u
m
i
n
g
m
o
r
e
ti
m
e
to
clas
s
i
f
y
th
e
r
i
g
h
t
d
is
ea
s
es.
B
esid
es
th
at,
d
if
f
er
e
n
t
d
is
e
ases
h
a
v
e
d
i
f
f
er
e
n
t
w
a
y
s
to
h
an
d
le
it.
Ne
w
d
is
ea
s
e
th
at
ca
n
b
e
v
is
u
all
y
s
p
o
t
it
s
y
m
p
to
m
s
m
a
y
r
eq
u
ir
e
t
h
e
lea
v
es
to
b
e
test
i
n
t
h
e
lab
o
r
ato
r
y
an
d
r
eq
u
ir
e
a
w
ee
k
o
r
m
a
y
b
e
a
m
o
n
th
to
d
etec
t
it.
So
,
it
is
n
ec
ess
ar
y
to
d
ev
el
o
p
a
s
y
s
te
m
t
h
at
i
s
ab
le
to
ass
is
t
t
h
e
w
o
r
k
er
i
n
t
h
e
o
il
p
al
m
p
lan
tatio
n
ar
ea
in
d
eter
m
i
n
in
g
t
h
e
s
p
ec
i
f
ic
d
is
ea
s
e
s
y
m
p
to
m
s
o
n
t
h
e
o
il
p
al
m
tr
ee
.
T
h
is
s
y
s
te
m
w
i
l
l
h
elp
t
h
e
w
o
r
k
er
to
d
eter
m
i
n
e
th
e
s
y
m
p
to
m
s
ac
c
u
r
atel
y
in
a
s
h
o
r
t
ti
m
e
p
er
io
d
.
T
h
er
ef
o
r
e,
in
t
h
is
w
o
r
k
S
VM
h
as
b
ee
n
u
s
ed
a
s
a
cla
s
s
i
f
ier
t
o
id
en
ti
f
y
an
d
cla
s
s
i
f
y
t
h
e
d
is
ea
s
e
i
n
f
ec
t
io
n
b
ase
d
o
n
s
p
o
t th
at
r
ef
lec
t th
e
d
is
ea
s
e
s
o
f
C
h
i
m
ae
r
a
an
d
A
n
t
h
r
ac
n
o
s
e.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
er
e
ar
e
f
iv
e
m
ai
n
s
tep
s
u
s
e
d
f
o
r
class
i
f
icatio
n
o
f
p
al
m
o
il
leaf
d
is
ea
s
e
s
as
s
h
o
w
n
in
F
ig
u
r
e
1
.
T
h
e
o
v
er
all
class
i
f
icat
io
n
co
n
s
is
t
s
o
f
i
m
a
g
e
ac
q
u
i
s
itio
n
th
r
o
u
g
h
d
ig
ita
l
ca
m
er
a,
i
m
ag
e
e
n
h
a
n
ce
m
e
n
t,
cl
u
s
ter
i
n
g
an
d
clas
s
if
icatio
n
.
B
y
g
o
i
n
g
t
h
r
o
u
g
h
t
h
i
s
p
r
o
ce
s
s
es,
t
h
e
p
r
esen
ce
o
f
d
is
ea
s
es
o
n
t
h
e
p
al
m
o
il
leaf
ca
n
b
e
id
en
ti
f
ied
.
Fig
u
r
e
1
.
T
h
e
o
v
er
all
p
r
o
ce
s
s
o
f
d
is
ea
s
e
clas
s
i
f
icatio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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&
C
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2502
-
4752
C
la
s
s
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fica
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f D
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fr
o
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I
ma
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P
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Tech
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(
Ma
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Md
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193
2
.
1
.
I
m
a
g
e
a
cquis
it
io
n
T
h
e
i
m
ag
e
s
u
s
ed
in
th
i
s
w
o
r
k
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ta
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en
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w
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e
leaf
o
f
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il
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ee
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T
h
e
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e
tak
en
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it
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a
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KON
d
i
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ital
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m
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a.
T
h
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a
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.
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s
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ith
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h
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te
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ac
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r
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Fig
u
r
e
2
s
h
o
w
s
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e
s
a
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p
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i
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a
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es
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s
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.
Fig
u
r
e
2
.
Sa
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o
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d
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f
er
en
t p
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m
o
il lea
f
2
.
2
.
I
m
a
g
e
E
nh
a
nce
m
ent
T
h
er
e
ar
e
v
ar
io
u
s
tech
n
iq
u
e
i
n
i
m
a
g
e
en
h
an
ce
m
e
n
t
s
u
ch
a
s
co
n
s
tr
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en
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ilter
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e
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ased
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s
s
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g
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d
i
m
a
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e
ar
ith
m
etic.
Ho
wev
er
,
in
t
h
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p
r
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j
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t
th
e
i
m
ag
e
e
n
h
an
ce
m
e
n
t
tec
h
n
iq
u
e
th
at
w
as
u
s
ed
w
as
o
n
l
y
co
n
tr
ast
en
h
a
n
ce
m
en
t.
T
h
e
co
n
tr
ast
e
n
h
a
n
ce
m
e
n
t
w
a
s
d
o
n
e
to
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ed
u
ce
t
h
e
n
o
i
s
es
in
t
h
e
i
m
a
g
e
w
h
ich
m
a
k
e
t
h
e
r
eg
io
n
o
f
in
ter
est
o
f
th
e
i
m
a
g
e
n
o
t
clea
r
th
a
t
ca
n
lead
to
th
e
q
u
alit
y
o
f
th
e
i
m
ag
e
d
r
o
p
p
ed
s
o
th
at
th
e
q
u
alit
y
o
f
th
e
i
m
ag
e
w
il
l
b
e
im
p
r
o
v
e
[
1
2
]
.
T
h
is
tech
n
iq
u
e
w
il
l a
d
j
u
s
t th
e
i
m
a
g
e
in
te
n
s
it
y
v
alu
e
s
o
r
co
lo
u
r
m
ap
.
2
.
3
.
Clus
t
er
ing
T
ec
hn
i
qu
e
Seg
m
en
tatio
n
i
s
d
o
n
e
th
r
o
u
g
h
clu
s
ter
i
n
g
[
1
3
]
.
A
b
asic
cl
u
s
ter
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n
g
k
-
m
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alg
o
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r
s
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m
e
n
tatio
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in
tex
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ed
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es
[
1
4
]
.
I
t
clu
s
ter
s
t
h
e
r
elate
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p
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els
to
s
eg
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e
n
t
t
h
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i
m
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g
e.
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m
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n
tatio
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d
o
n
e
th
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f
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n
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e
ch
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co
r
d
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to
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e
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o
lo
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r
co
m
p
o
n
en
t
s
.
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m
en
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s
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ep
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in
g
o
n
t
h
e
ch
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ter
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s
tics
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m
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2
.
4
.
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s
s
if
ica
t
io
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C
las
s
i
f
ier
is
u
s
ed
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n
g
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m
ag
e
s
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ased
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n
t
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eir
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at
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r
es.
Su
p
p
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r
t
v
ec
to
r
m
a
h
i
n
e
(
S
VM
)
w
as
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r
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p
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w
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lem
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u
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al
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n
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ak
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.
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h
e
s
o
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t
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ar
e
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a
s
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n
M
A
T
L
A
B
.
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n
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h
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ain
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d
test
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ed
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ch
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o
r
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a
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ial
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asis
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u
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e
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r
al
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et
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k
s
a
n
d
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p
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r
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ec
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ac
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e.
SV
M
h
as
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ee
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also
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o
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n
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e
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e
f
f
icie
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t c
las
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i
f
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o
f
leaf
d
is
ea
s
e
[
1
5
]
,
[
1
6
]
.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
I
n
t
h
is
w
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k
,
t
h
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d
ata
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et
u
s
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llected
f
r
o
m
T
ap
ak
Se
m
ai
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Fe
lcr
a
in
Se
n
d
a
y
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n
Ne
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er
i
Se
m
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ila
n
f
o
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s
ed
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th
e
m
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s
t
co
m
m
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n
d
is
ea
s
e
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i
n
f
ec
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p
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m
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il
lea
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ich
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e
C
h
i
m
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r
a
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d
An
t
h
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ac
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d
is
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h
e
C
h
i
m
ae
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a
d
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is
ca
u
s
ed
b
y
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e
g
e
n
etic
p
r
o
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lem
o
f
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e
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p
al
m
tr
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ee
d
s
.
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h
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s
y
m
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s
o
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e
d
i
s
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s
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v
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ip
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r
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f
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r
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er
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ta
g
e
in
p
al
m
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il
p
l
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tatio
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.
Fig
u
r
e
4
s
h
o
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th
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s
y
m
p
to
m
s
o
f
th
e
C
h
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m
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r
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I
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.
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y
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e
An
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h
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as sh
o
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m
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as i
n
Fi
g
u
r
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5
.
Fig
u
r
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5
.
An
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s
e
s
y
m
p
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s
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f
3
.
1
.
I
m
a
g
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a
cquis
it
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n
T
h
is
s
a
m
p
le
i
m
a
g
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to
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e
M
A
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L
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B
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t
w
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e
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al
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e
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th
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etec
tio
n
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f
icatio
n
o
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p
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il
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ee
d
is
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A
f
ter
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s
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cted
s
a
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p
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M
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B
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t
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s
s
t
h
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m
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h
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im
a
g
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4
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.
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h
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w
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ize
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ize
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if
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u
l
t
p
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.
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ased
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Fi
g
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r
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6
r
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ep
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ac
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s
a
m
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g
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th
at
w
a
s
u
s
ed
in
t
h
is
cla
s
s
i
f
icatio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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esia
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2502
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y
th
e
C
h
im
ae
r
a
an
d
A
n
th
r
ac
n
o
s
e
s
y
m
p
to
m
s
.
I
t
s
h
o
w
s
th
at
th
e
ac
cu
r
a
cy
ac
h
iev
ed
f
o
r
C
h
im
ae
r
a
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9
7
%
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h
ile
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ac
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r
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cy
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f
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n
th
r
ac
n
o
s
e
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9
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%.
ACK
NO
WL
E
D
G
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M
E
NT
T
h
e
au
th
o
r
s
w
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ld
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p
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atit
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e
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n
t
er
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at
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al
I
s
la
m
ic
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n
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er
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it
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la
y
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ia,
w
h
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h
h
as
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r
o
v
id
ed
f
u
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d
in
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f
o
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th
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ch
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h
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g
h
R
I
GS1
6
-
087
-
0251
.
T
h
e
au
th
o
r
s
also
w
o
u
ld
li
k
e
t
o
ex
p
r
ess
s
p
ec
ial
t
h
an
k
s
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d
g
r
a
titu
d
e
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th
e
U
n
i
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er
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iti T
ek
n
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i M
A
R
A
f
o
r
th
e
s
u
p
p
o
r
t.
RE
F
E
R
E
NC
E
S
[1
]
L
a
il
a
N
.
,
e
t
a
l
.
,
“
Iss
u
e
s
o
f
G
a
n
o
d
e
rm
a
sp
p
.
A
n
d
Ba
sa
l
S
tem
Ro
t
Dise
a
se
M
a
n
a
g
e
m
e
n
t
in
Oil
P
a
l
m
,”
Ame
ric
a
n
J
o
u
rn
a
l
o
f
A
g
ric
u
lt
u
ra
l
S
c
ien
c
e
,
v
o
l/
issu
e
:
2
(3
)
,
p
p
.
1
0
3
-
1
0
7
,
2
0
1
5
.
[2
]
Ish
a
q
I
.
,
e
t
a
l.
,
“
De
tec
ti
o
n
o
f
Ba
sa
l
S
tem
Ro
t
Dise
a
se
a
t
Oil
P
a
lm
P
l
a
n
tatio
n
s Us
i
n
g
S
o
n
ic T
o
m
o
g
r
a
p
h
y
,”
J
o
u
rn
a
l
o
f
S
u
sta
in
a
b
il
it
y
S
c
ien
c
e
a
n
d
M
a
n
a
g
e
me
n
t
,
v
o
l/
issu
e
:
9
(2
)
,
p
p
.
52
-
57
,
2
0
1
4
.
[3
]
No
rsilan
I.
N
.
,
e
t
a
l.
,
“
Ef
f
e
c
t
o
f
F
o
rm
u
late
d
Bio
o
rg
a
n
ic
Co
n
t
a
in
in
g
Bu
rk
h
o
ld
e
ria
G
a
n
o
EB2
i
n
S
u
p
p
re
ss
in
g
G
a
n
o
d
e
r
m
a
Dise
a
se
in
Oil
P
a
lm
S
e
e
d
li
n
g
s
,”
Pl
a
n
t
Pr
o
tec
t
S
c
i
.
,
v
o
l/
issu
e
:
5
1
(2
)
,
p
p
.
80
–
87
,
2
0
1
5
.
[4
]
L
iag
h
a
t
S
.
,
e
t
a
l.
,
“
Early
De
tec
ti
o
n
Of
Oil
P
a
lm
F
u
n
g
a
l
Dise
a
se
In
f
e
sta
ti
o
n
Us
in
g
A
M
id
-
In
f
ra
re
d
S
p
e
c
tro
sc
o
p
y
T
e
c
h
n
iq
u
e
,”
2
0
1
1
.
[5
]
He
ri
S
.
,
e
t
a
l.
,
“
M
a
p
p
in
g
a
n
d
i
d
e
n
ti
fy
in
g
b
a
sa
l
ste
m
ro
t
d
ise
a
se
in
o
il
p
a
lm
s
in
No
rt
h
S
u
m
a
tra
w
it
h
Qu
ick
Bird
im
a
g
e
r
,”
Pre
c
isio
n
Ag
ric
.
,
v
o
l.
12
,
p
p
.
2
3
3
–
2
4
8
,
2
0
1
0
.
[6
]
A
rti
N.
R
.
,
e
t
a
l.
,
“
Im
a
g
e
p
ro
c
e
ss
in
g
T
e
c
h
n
iq
u
e
s
f
o
r
De
tec
ti
o
n
o
f
Lea
f
Dise
a
s
e
,”
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ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Ad
v
a
n
c
e
d
Res
e
a
rc
h
in
C
o
mp
u
ter
S
c
ien
c
e
a
n
d
S
o
ft
w
a
re
En
g
in
e
e
rin
g
,
v
o
l/
iss
u
e
:
3
(1
1
)
,
p
p
.
3
9
7
-
3
9
9
,
2
0
1
3
.
[7
]
L
e
a
v
li
n
e
E.
J
.
a
n
d
D.
S
in
g
h
A
.
A.
G.
,
“
On
Tea
c
h
in
g
Di
g
it
a
l
I
m
a
g
e
P
ro
c
e
ss
in
g
w
it
h
M
ATLA
B
,”
Am
e
ric
a
n
J
o
u
rn
a
l
o
f
S
ig
n
a
l
Pro
c
e
ss
in
g
,
v
o
l/
issu
e
:
4
(1
)
,
p
p
.
7
-
15
,
2
0
1
4
.
[8
]
G
o
n
z
a
lez
R.
C
.
,
e
t
a
l.
,
“
Dig
it
a
l
ima
g
e
p
ro
c
e
ss
in
g
u
sin
g
M
A
TL
A
B
,”
P
e
a
rso
n
E
d
u
c
a
ti
o
n
I
n
d
ia
,
2
0
0
8
.
[9
]
V
a
p
n
ik
V.
,
“
S
tatisti
c
a
l
L
e
a
rn
in
g
T
h
e
o
r
y
,”
W
il
e
y
,
N
e
w
Yo
rk
,
1
9
9
8
.
[1
0
]
A
le
x
a
n
d
ro
s K
.
,
e
t
a
l.
,
“
V
e
c
to
r
M
a
c
h
in
e
s
,”
in
R.
J
o
u
rn
a
l
o
f
S
ta
ti
st
ica
l
S
o
ft
w
a
re
,
v
o
l/
issu
e
:
1
5
(
9
)
,
2
0
0
6
.
[1
1
]
Ra
k
e
sh
C
.
,
e
t
a
l.
,
“
De
tec
ti
o
n
a
n
d
Re
c
o
g
n
it
io
n
o
f
L
e
a
f
Dise
a
s
e
u
si
n
g
I
m
a
g
e
P
ro
c
e
ss
in
g
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
En
g
i
n
e
e
rin
g
S
t
u
d
ies
a
n
d
Co
m
p
u
ti
n
g
,
v
o
l/
issu
e
:
7
(5
)
,
p
p
.
1
1
9
6
4
-
1
1
9
6
7
,
2
0
1
7
.
[1
2
]
A
rti
N.
R
.
,
e
t
a
l
.,
“
L
e
a
f
Dise
a
se
De
tec
ti
o
n
Us
in
g
Im
a
g
e
P
ro
c
e
ss
in
g
a
n
d
Ne
u
ra
l
Ne
tw
o
rk
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Ad
v
a
n
c
e
E
n
g
i
n
e
e
r in
g
a
n
d
Res
e
a
rc
h
De
v
e
lo
p
me
n
t
(
IJ
AE
RD)
,
v
o
l/
i
ss
u
e
:
1
(6
)
,
2
0
1
4
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
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m
p
Sci,
Vo
l
.
10
,
No
.
1
,
A
p
r
il
2
0
1
8
:
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9
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–
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200
[1
3
]
Ha
ig
u
a
n
g
W
.
,
e
t
a
l.
,
“
Im
a
g
e
Re
c
o
g
n
it
io
n
o
f
P
lan
t
Dise
a
se
s
Ba
se
d
o
n
Ba
c
k
-
p
ro
p
a
g
a
ti
o
n
Ne
tw
o
rk
s
,”
5
th
In
ter
n
a
t
io
n
a
l
C
o
n
g
re
ss
o
n
Ima
g
e
a
n
d
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
.
C
h
o
n
g
q
i
n
g
,
Ch
in
a
,
2
0
1
2
.
[1
4
]
M
o
k
h
led
S
.
a
n
d
Al
-
T
a
r
a
w
n
e
h
,
“
A
n
Em
p
iri
c
a
l
In
v
e
stig
a
ti
o
n
o
n
Oliv
e
L
e
a
v
e
S
p
o
t
Dise
a
se
u
sin
g
A
u
to
-
Cro
p
p
i
n
g
S
e
g
m
e
n
tatio
n
a
n
d
F
u
z
z
y
C
-
M
e
a
n
s
Clas
sif
ica
ti
o
n
,”
W
o
rld
Ap
p
li
e
d
S
c
ien
c
e
s
J
o
u
rn
a
l
,
v
o
l/
issu
e
:
2
3
(9
)
,
p
p
.
1
2
0
7
-
1
2
1
1
,
2
0
1
3
.
[1
5
]
Kira
n
R.
G
.
a
n
d
Ujwa
ll
a
G
.
,
“
A
n
Ov
e
rv
ie
w
o
f
th
e
Re
s
e
a
rc
h
o
n
P
la
n
t
L
e
a
v
e
s
Dise
a
d
e
tec
ti
o
n
u
sin
g
Im
a
g
e
P
r
o
c
e
ss
in
g
T
e
c
h
n
iq
u
e
s,
”
IOS
R
J
o
u
rn
a
l
o
f
Co
mp
u
ter
E
n
g
i
n
e
e
rin
g
,
v
o
l/
issu
e
:
1
6
(
1
)
,
p
p
.
10
-
16
,
2
0
1
4
.
[1
6
]
N.
D.
Ka
rti
k
a
,
e
t
a
l.
,
“
Oil
P
a
lm
Yie
ld
F
o
re
c
a
stin
g
Ba
se
d
o
n
W
e
a
th
e
r
V
a
riab
les
Us
in
g
A
rti
f
icia
l
Ne
u
ra
l
Ne
tw
o
rk
,”
In
d
o
n
e
sia
n
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
,
v
o
l/
iss
u
e
:
3
(
3
),
p
p
.
626
-
6
3
3
,
2
0
1
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.