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8708
I
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6
,
Decem
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2020
:
6
5
3
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-
6
5
4
0
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it
h
tr
ad
itio
n
al
a
g
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icu
l
tu
r
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d
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elo
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S
m
ar
t a
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ates
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m
ate
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to
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la
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t o
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in
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-
C
o
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n
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ltip
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tr
o
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ea
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s
e
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y
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te
m
s
p
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d
u
ce
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ip
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tco
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i.e
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in
cr
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r
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ctiv
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en
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a
n
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t
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a
y
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o
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iev
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a
ll
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ee
at
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en
t
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is
a
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ee
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o
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i
m
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tatio
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ad
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-
C
S
A
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ai
n
tai
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s
ec
o
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s
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s
s
er
v
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T
h
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y
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m
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ad
o
p
t
a
lan
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s
ca
p
e
ap
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u
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s
u
p
o
n
th
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p
r
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les o
f
s
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tai
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ain
tain
in
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t
h
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ec
o
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.
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S
A
h
as
m
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ltip
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en
tr
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p
o
in
t
s
at
d
if
f
er
en
t
le
v
el
s
:
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te
m
s
ca
n
h
a
v
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m
u
lt
ip
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en
tr
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o
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ts
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an
g
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f
r
o
m
t
h
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d
ev
elo
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m
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t
o
f
tec
h
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lo
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n
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p
r
ac
tices
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cli
m
ate
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o
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m
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in
s
u
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x
p
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S
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icial
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tio
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T
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ex
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ex
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F
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F
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Mo
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2.
RE
L
AT
E
D
WO
RK
S
T
an
et
al
.
,
[
1
]
,
s
tated
th
at
th
e
r
esear
ch
o
n
A
I
h
as
t
h
e
tr
e
m
en
d
o
u
s
e
f
f
ec
t
s
o
n
t
h
e
v
ar
io
u
s
f
ield
s
lik
e
m
ilit
ar
ie
s
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m
ed
icals,
c
h
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m
i
s
tr
y
,
e
n
g
i
n
ee
r
i
n
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,
m
an
a
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m
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t
,
m
a
n
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f
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r
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etc.
T
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ls
o
m
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tio
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t
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A
I
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s
t
h
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w
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t
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tec
h
n
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lo
g
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ev
elo
p
m
en
t
b
y
d
e
f
in
in
g
v
ar
io
u
s
f
o
r
m
s
o
f
i
m
p
le
m
en
tat
io
n
s
lik
e
f
u
zz
y
lo
g
ic,
n
eu
r
al
n
et
w
o
r
k
,
r
u
le
-
b
ased
e
x
p
er
t
s
y
s
te
m
,
f
r
a
m
e
-
b
ased
ex
p
er
t
s
y
s
te
m
,
g
e
n
etic
al
g
o
r
ith
m
,
etc.
T
h
ey
p
r
ese
n
ted
t
h
e
s
tate
m
en
t
s
t
h
at
A
I
r
esear
c
h
a
n
d
ap
p
licatio
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s
i
s
g
o
in
g
to
r
ep
lace
t
h
e
h
u
m
a
n
e
x
p
er
ts
w
it
h
th
e
lates
t in
n
o
v
atio
n
s
i
n
t
h
e
te
ch
n
o
lo
g
y
.
B
ass
e
m
et
al
.
,
[
2
]
,
p
r
o
p
o
s
ed
a
n
E
x
p
er
t
S
y
s
te
m
d
es
ig
n
w
h
ic
h
is
u
s
ed
to
h
elp
f
ar
m
er
s
f
o
r
d
iag
n
o
s
i
n
g
w
ater
m
elo
n
d
is
ea
s
e
s
n
a
m
el
y
P
o
w
d
er
y
m
i
ld
e
w
,
Do
w
n
y
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ild
e
w
,
A
l
ter
n
ar
ia
lea
f
s
p
o
t,
A
n
t
h
r
ac
n
o
s
e,
Fu
s
ar
iu
m
w
il
t
a
n
d
C
u
cu
m
b
er
m
o
s
aic
d
is
ea
s
e.
T
h
e
y
d
esi
g
n
ed
an
e
x
p
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t
s
y
s
te
m
w
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h
p
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ese
n
ts
an
i
n
f
o
r
m
atio
n
o
n
w
ater
m
elo
n
d
is
ea
s
es,
ca
u
s
e
s
an
d
th
e
tr
ea
t
m
en
t
o
f
d
is
ea
s
e
u
s
i
n
g
E
-
c
lip
s
E
x
p
er
t
S
y
s
te
m
lan
g
u
ag
e
an
d
ev
alu
a
ted
w
i
th
a
g
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u
p
o
f
f
ar
m
er
s
to
id
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ti
f
y
th
e
p
er
f
o
r
m
an
ce
.
Sab
zi
et
al
.
,
[
3
]
,
d
is
cu
s
s
ed
ab
o
u
t
th
e
P
r
ec
is
io
n
Ag
r
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lt
u
r
e
w
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er
e
th
e
g
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s
is
to
id
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if
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to
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m
o
v
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w
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d
s
in
telli
g
en
tl
y
,
w
h
er
e
h
er
b
icid
es
ca
n
b
e
s
p
r
a
y
ed
o
n
l
y
i
n
w
ee
d
s
ex
i
s
ti
n
g
ar
ea
s
b
y
r
ed
u
ci
n
g
th
e
d
o
s
ag
e
o
f
h
er
b
icid
es
to
a
v
o
id
h
ar
m
f
u
l
ef
f
ec
t
s
.
T
h
e
y
p
r
es
en
ted
a
co
m
p
u
ter
v
is
io
n
b
ased
ex
p
er
t
s
y
s
t
e
m
f
o
r
id
en
ti
f
y
i
n
g
p
o
tato
p
lan
ts
a
n
d
t
h
r
ee
d
if
f
er
en
t
k
i
n
d
s
o
f
w
ee
d
s
to
p
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f
o
r
m
s
ite
-
s
p
ec
i
f
ic
s
p
r
a
y
i
n
g
.
T
h
e
y
p
r
ese
n
ted
v
is
u
aliza
t
io
n
o
f
ag
r
ic
u
lt
u
r
e
t
h
r
o
u
g
h
lo
n
g
it
u
d
e
a
n
d
latit
u
d
e
p
o
s
itio
n
i
n
g
f
o
r
id
en
tify
i
n
g
t
h
e
o
b
j
ec
ts
u
s
i
n
g
i
m
a
g
e
p
r
o
ce
s
s
in
g
,
t
h
e
y
e
x
tr
ac
ted
3
4
5
9
o
b
j
ec
ts
to
tr
ain
an
d
test
th
e
class
i
f
ier
s
w
it
h
1
2
6
co
lo
r
f
ea
tu
r
es
an
d
6
0
tex
tu
r
e
f
ea
t
u
r
es
f
r
o
m
ea
c
h
o
b
j
ec
t.
T
h
e
y
u
s
ed
t
w
o
m
e
tah
e
u
r
is
t
ic
al
g
o
r
ith
m
s
to
o
p
ti
m
ize
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
a
n
e
u
r
al
n
et
w
o
r
k
clas
s
if
ier
:
n
a
m
el
y
,
th
e
cu
lt
u
r
al
alg
o
r
it
h
m
,
h
ar
m
o
n
y
s
ea
r
ch
al
g
o
r
it
h
m
f
o
r
th
e
o
p
ti
m
al
co
n
f
i
g
u
r
atio
n
o
f
th
e
n
e
t
w
o
r
k
an
d
t
h
e
n
a
s
tati
s
t
ical
m
et
h
o
d
b
ased
o
n
lin
ea
r
d
is
cr
i
m
i
n
a
n
t
a
n
al
y
s
is
i
s
u
s
ed
f
o
r
th
e
ex
p
er
i
m
e
n
tal
ev
alu
a
tio
n
.
B
an
n
er
j
ee
et
al
.
,
[
4
]
,
p
r
esen
ted
a
s
u
r
v
e
y
o
n
t
h
e
ap
p
licatio
n
s
o
f
ar
ti
f
icial
i
n
telli
g
e
n
ce
tec
h
n
iq
u
es
i
n
ag
r
icu
l
tu
r
e
ad
d
r
ess
i
n
g
s
ev
er
al
is
s
u
es
li
k
e
cr
o
p
m
a
n
ag
e
m
e
n
t,
s
o
il
m
a
n
ag
e
m
e
n
t,
w
ee
d
m
an
a
g
e
m
e
n
t
etc,
w
h
ic
h
lead
s
to
s
ev
er
e
cr
o
p
lo
s
s
alo
n
g
w
it
h
e
n
v
ir
o
n
m
e
n
tal
h
az
ar
d
s
m
a
y
b
e
d
u
e
to
e
x
ce
s
s
iv
e
u
s
e
o
f
ch
e
m
ical
s
.
Se
v
er
al
r
esear
ch
es
h
a
v
e
b
ee
n
c
o
n
d
u
ct
ed
to
a
d
d
r
ess
th
ese
is
s
u
es.
T
h
e
y
p
r
esen
ted
v
ar
io
u
s
co
n
tr
ib
u
tio
n
s
o
f
ar
tif
ic
ial
in
telli
g
e
n
ce
r
elate
d
to
ag
r
icu
ltu
r
e
co
v
er
in
g
t
h
e
d
o
m
ai
n
s
an
d
d
o
m
ai
n
s
to
p
r
o
v
id
e
in
f
o
r
m
at
io
n
o
n
a
g
r
o
-
in
telli
g
e
n
t s
y
s
te
m
s
.
R
av
i
s
an
k
ar
et
al
.
,
[
5
]
,
p
r
esen
t
ed
an
w
eb
b
ased
ex
p
er
t
s
y
s
te
m
d
esi
g
n
f
o
r
t
h
e
id
en
ti
f
icat
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n
o
f
i
n
s
ec
t
/p
est
m
a
n
a
g
e
m
en
t
o
n
t
h
e
cr
o
p
b
y
d
iag
n
o
s
i
n
g
th
e
p
r
o
b
lem
to
m
i
n
i
m
ize
t
h
e
y
ield
lo
s
s
es.
T
h
e
ex
p
er
i
m
e
n
tatio
n
is
ca
r
r
ied
o
u
t
o
n
t
h
e
to
b
ac
co
cr
o
p
.
T
h
e
m
o
d
el
d
esi
g
n
ed
b
y
th
e
m
i
s
p
r
ese
n
ted
as
Ag
r
id
ak
s
h
,
u
s
i
n
g
o
n
to
lo
g
y
b
ased
m
et
h
o
d
s
f
o
r
th
e
e
f
f
ec
ti
v
e
id
en
ti
f
icatio
n
an
d
m
a
n
ag
e
m
en
t
o
f
p
ests
.
T
h
e
k
n
o
w
led
g
e
m
o
d
el
i
s
d
esi
g
n
e
d
f
o
r
th
e
ef
f
icie
n
t
k
n
o
w
led
g
e
ac
q
u
is
itio
n
,
k
n
o
w
led
g
e
r
etr
iev
a
l p
r
o
ce
s
s
.
Nip
u
n
et
al
.,
[
6
]
,
p
r
esen
te
d
th
e
s
m
ar
t
a
g
r
ic
u
lt
u
r
e
co
n
ce
p
t
u
s
i
n
g
I
OT
,
u
s
in
g
A
r
d
u
in
o
k
it
.
T
h
ey
p
r
o
p
o
s
ed
a
m
o
d
el
w
i
th
t
e
m
p
er
atu
r
e
s
e
n
s
o
r
s
,
r
ad
ar
s
en
s
o
r
s
f
o
r
o
p
ti
m
izi
n
g
w
a
ter
u
s
a
g
e
an
d
y
ield
a
n
d
also
ad
o
p
ted
s
m
ar
t
w
ater
m
an
a
g
e
m
en
t
s
y
s
te
m
s
w
it
h
co
n
s
i
s
te
n
t
m
o
n
ito
r
i
n
g
o
f
w
ea
t
h
er
co
n
d
iti
o
n
s
.
T
h
e
s
etu
p
also
r
ep
r
esen
ts
a
p
ar
t
o
f
g
r
id
w
h
i
ch
u
tili
ze
s
s
o
lar
e
n
er
g
y
to
p
r
ev
en
t
b
atter
y
lo
s
s
w
it
h
a
m
i
n
iat
u
r
e
s
o
lar
f
ar
m
.
T
h
ey
ad
o
p
ted
m
ac
h
i
n
e
lear
n
in
g
alg
o
r
it
h
m
s
an
d
I
OT
to
h
an
d
le
th
e
p
r
o
b
lem
s
r
elate
d
to
w
ate
r
an
d
en
er
g
y
.
Sar
k
er
et
al
.
,
[
7
]
ad
o
p
ted
C
NN
m
o
d
els
f
r
o
m
m
ac
h
in
e
to
h
a
n
d
le
co
m
p
le
x
i
m
ag
e
d
ete
ctio
n
p
r
o
b
lem
s
.
T
h
ey
u
s
ed
a
r
eg
io
n
-
b
ased
,
f
u
l
l
y
co
n
v
o
lu
tio
n
al
n
e
t
w
o
r
k
,
f
o
r
p
r
o
ce
s
s
in
g
f
as
t
an
d
ac
cu
r
ate
o
b
j
ec
t
d
etec
tio
n
o
n
th
e
cr
o
p
s
.
T
h
e
y
s
tated
th
at
th
e
d
e
ep
r
esid
u
al
n
et
w
o
r
k
s
(
R
e
s
Nets)
ca
n
p
r
o
ce
s
s
th
e
tr
ain
i
n
g
p
r
o
ce
s
s
f
aster
an
d
attain
h
ig
h
ac
c
u
r
ac
y
t
h
an
tr
a
d
itio
n
al
co
n
v
e
n
tio
n
al
n
e
u
r
al
n
et
w
o
r
k
s
.
T
h
ey
u
s
ed
d
ee
p
r
esid
u
al
n
et
w
o
r
k
f
o
r
h
an
d
li
n
g
th
e
o
v
er
-
f
itti
n
g
p
r
o
b
l
e
m
as
w
ell
a
s
d
ata
au
g
m
e
n
tati
o
n
w
ith
R
esNe
t to
id
en
ti
f
y
t
h
e
w
ee
d
s
i
n
th
e
cr
o
p
.
Ha
w
a
s
h
in
et
al
.
,
[
8
]
,
p
r
esen
ted
th
e
i
m
p
o
r
tan
ce
o
f
s
m
ar
t
a
g
r
icu
lt
u
r
e
an
d
p
r
o
v
id
ed
th
e
id
eo
lo
g
y
f
o
r
m
an
a
g
i
n
g
th
e
w
ater
r
eso
u
r
ce
m
a
n
a
g
e
m
en
t
i
n
th
e
ag
r
ic
u
lt
u
r
e.
T
h
ey
ad
ap
ted
th
e
I
Ot
w
it
h
t
h
e
v
is
io
n
o
f
m
u
lti
m
ed
ia
i.e
,
I
n
ter
n
et
o
f
m
u
lti
m
ed
ia
th
in
g
s
(
I
o
MT
)
to
o
p
ti
m
ize
t
h
e
ir
r
ig
atio
n
p
r
o
ce
s
s
w
it
h
t
h
e
h
elp
o
f
m
u
lti
m
ed
ia
s
e
n
s
o
r
s
.
T
h
e
y
in
clu
d
ed
i
m
a
g
e
p
r
o
ce
s
s
i
n
g
an
d
m
ac
h
in
e
lear
n
i
n
g
s
tr
ateg
ie
s
alo
n
g
w
it
h
I
OT
to
p
er
f
o
r
m
t
h
e
o
p
ti
m
ized
ir
r
ig
ati
o
n
p
r
o
ce
s
s
.
Fieh
n
et
al
.
,
[
9
]
,
d
is
cu
s
s
ed
th
e
r
o
le
o
f
S
m
ar
t
f
ar
m
in
g
as
a
n
ec
o
n
o
m
ic
w
a
y
o
f
a
g
r
icu
l
tu
r
e
ad
o
p
tin
g
th
e
latest
tec
h
n
o
lo
g
ies
li
k
e
I
OT
allo
w
i
n
g
m
o
r
e
n
u
m
b
er
o
f
ch
o
ices
i
n
d
esi
g
n
i
n
g
th
e
o
p
ti
m
al
s
o
l
u
tio
n
f
o
r
v
ar
io
u
s
c
h
alle
n
g
e
s
.
T
h
e
y
d
esig
n
ed
t
h
e
s
tr
ateg
ical
s
o
lu
t
io
n
u
s
in
g
m
ac
h
i
n
e
lear
n
i
n
g
to
h
an
d
le
th
e
w
ater
s
u
p
p
l
y
ir
r
esp
ec
tiv
e
o
f
cli
m
ate
ch
a
n
g
es.
T
h
e
y
u
s
ed
R
F,
So
lar
e
n
er
g
y
w
it
h
v
ar
io
u
s
s
en
s
o
r
s
a
n
d
a
ctu
ato
r
s
to
p
er
f
o
r
m
th
e
m
o
n
ito
r
i
n
g
p
r
o
ce
s
s
.
L
a
ter
th
e
y
u
s
ed
C
o
n
v
o
l
u
tio
n
al
n
e
u
r
al
n
et
w
o
r
k
f
o
r
p
er
f
o
r
m
i
n
g
t
h
e
d
ata
f
lo
w
co
n
tr
o
l.
J
h
a
,
et
al
.
,
[
1
0
,
11
]
,
p
r
esen
ted
th
e
s
u
r
v
e
y
o
n
v
ar
io
u
s
p
r
o
b
le
m
s
t
h
at
w
ill
ar
is
e
f
o
r
a
cr
o
p
in
ag
r
icu
lt
u
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b
y
ch
o
o
s
in
g
t
h
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g
r
ap
e
cr
o
p
.
T
h
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y
al
s
o
d
is
c
u
s
s
ed
ab
o
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t
v
ar
i
o
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s
c
h
alle
n
g
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s
t
h
at
ar
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r
ec
o
g
n
ized
in
t
h
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cr
o
p
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a
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m
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v
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ac
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lear
n
i
n
g
s
tr
ateg
ies
t
h
at
c
an
b
e
ap
p
lied
f
o
r
ef
f
ec
ti
v
e
o
r
s
m
ar
t
ag
r
ic
u
lt
u
r
e
ap
p
licatio
n
.
T
h
e
y
g
av
e
th
e
id
eo
lo
g
y
o
f
u
s
i
n
g
m
u
lt
ip
le
s
tr
at
eg
ies
to
in
v
o
k
e
s
o
l
u
tio
n
s
f
o
r
h
an
d
li
n
g
d
i
f
f
er
e
n
t
f
o
r
m
s
o
f
ch
alle
n
g
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
6
,
Decem
b
er
2020
:
6
5
3
1
-
6
5
4
0
6534
3.
ARCH
I
T
E
C
T
UR
E
T
h
e
ar
ch
itectu
r
e
o
f
th
e
p
r
o
p
o
s
ed
w
o
r
k
is
p
r
esen
ted
in
F
ig
u
r
e
4
.
T
h
e
A
r
ch
itect
u
r
e
ca
n
b
e
ex
p
lain
ed
in
4
s
tag
es
n
a
m
e
l
y
ac
q
u
is
it
io
n
,
v
alid
atio
n
,
q
u
er
y
p
r
o
ce
s
s
i
n
g
a
n
d
p
r
esen
tatio
n
.
a.
A
cq
u
is
it
io
n
:
T
h
is
s
ta
g
e
is
co
n
s
id
er
ed
f
o
r
o
b
tain
in
g
t
h
e
cr
o
p
i
m
a
g
es
f
r
o
m
v
ar
io
u
s
s
o
u
r
ce
s
,
w
h
ic
h
ca
n
b
e
eith
er
ca
p
tu
r
ed
o
r
m
ai
n
tai
n
ed
as
a
d
ataset
b
y
th
e
ad
m
in
is
tr
ato
r
o
r
th
e
f
ar
m
er
w
h
o
ca
p
tu
r
es
th
e
i
m
ag
e
o
f
ef
f
ec
ted
ar
ea
o
f
th
e
cr
o
p
u
s
i
n
g
ca
p
tu
r
in
g
d
e
v
ices.
T
h
e
i
m
a
g
e
s
ca
p
tu
r
ed
f
r
o
m
v
ar
io
u
s
s
o
u
r
c
es a
r
e
id
en
tifie
d
w
it
h
th
e
i
n
f
ec
ted
ar
ea
s
a
n
d
a
n
n
o
tated
w
it
h
th
e
i
n
f
o
r
m
atio
n
o
f
i
n
f
ec
tio
n
an
d
m
ai
n
tai
n
ed
a
s
a
d
ata
s
et
u
s
in
g
o
b
j
ec
t
r
ec
o
g
n
itio
n
[
12
]
tech
n
i
q
u
es.
I
f
th
e
i
m
a
g
e
is
a
test
i
m
ag
e,
t
h
en
t
h
e
an
n
o
tatio
n
s
ar
e
g
en
er
ated
an
d
v
er
if
ied
ac
r
o
s
s
t
h
e
s
et
o
f
tr
ain
i
n
g
i
m
a
g
es.
b.
Valid
atio
n
:
T
h
e
te
s
t
i
m
a
g
e
o
b
tain
ed
f
r
o
m
t
h
e
f
ar
m
er
is
v
e
r
if
ied
ac
r
o
s
s
th
e
s
et
o
f
i
m
a
g
e
s
i
n
t
h
e
tr
ai
n
i
n
g
d
ataset
alo
n
g
w
it
h
th
e
an
n
o
tatio
n
s
,
if
it
f
in
d
s
s
i
m
i
lar
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o
tatio
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alo
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g
w
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t
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ag
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s
th
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th
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co
r
r
esp
o
n
d
in
g
clas
s
o
f
in
f
ec
tio
n
s
ar
e
s
e
lecte
d
in
th
e
n
e
x
t
p
h
ase,
o
th
er
w
i
s
e
n
o
in
f
o
r
m
a
tio
n
is
p
r
o
v
id
ed
an
d
f
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ag
ai
n
f
o
r
t
h
e
r
eg
is
tr
ati
o
n
o
f
n
e
w
i
m
a
g
e
in
t
h
e
d
ataset
.
c.
Qu
er
y
P
r
o
ce
s
s
i
n
g
:
T
h
is
s
tag
e
d
ea
ls
w
ith
p
r
esen
ti
n
g
t
h
e
s
et
o
f
q
u
e
s
tio
n
s
r
elate
d
to
th
e
s
y
m
p
to
m
s
id
en
t
if
ied
o
n
th
e
cr
o
p
,
an
d
ap
p
ly
in
g
I
F
-
T
HE
N/Dec
is
io
n
R
u
le
s
o
n
th
e
m
p
r
o
v
id
es
t
h
e
i
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p
u
t
o
f
s
elec
t
in
g
t
h
e
clas
s
o
f
in
f
ec
tio
n
s
an
d
i
n
t
h
e
n
e
x
t
s
tag
e
d
etailed
i
n
f
o
r
m
atio
n
ab
o
u
t
th
e
in
f
ec
t
io
n
o
b
tain
ed
a
n
d
r
ea
s
o
n
s
f
o
r
o
cc
u
r
r
en
ce
an
d
p
r
ev
en
t
iv
e
m
e
asu
r
es i
s
p
r
o
v
id
ed
.
d.
P
r
esen
tatio
n
:
T
h
e
in
f
o
r
m
atio
n
ab
o
u
t
th
e
in
f
ec
t
io
n
o
cc
u
r
r
ed
an
d
r
ea
s
o
n
s
o
f
s
u
ch
i
n
f
ec
t
io
n
s
an
d
n
ec
ess
ar
y
p
r
ev
en
ti
v
e
m
ea
s
u
r
e
s
ar
e
d
is
p
la
y
ed
to
th
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1
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Ro
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P
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2020
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I
n
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&
C
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m
p
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I
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N:
2088
-
8708
A
n
effec
tive
id
en
tifi
ca
tio
n
o
f c
r
o
p
d
is
ea
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es u
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fa
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6537
4
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7
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Dis
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predict
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Af
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in
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s
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d
d
is
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s
[
2
1
-
25
]
d
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e
to
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ter
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f
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s
,
p
ests
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R
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
6
,
Decem
b
er
2020
:
6
5
3
1
-
6
5
4
0
6538
F
ig
u
r
e
8
.
Set o
f
in
f
ec
tio
n
s
w
it
h
r
esp
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t to
th
e
clas
s
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f
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F
ig
u
r
e
9
.
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f
q
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esti
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n
n
a
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g
en
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o
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th
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s
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ted
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b
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m
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f
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tio
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f
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if
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F
ig
u
r
e
10
.
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h
e
in
f
o
r
m
atio
n
ab
o
u
t th
e
s
e
lecte
d
in
f
ec
tio
n
i
s
p
r
esen
ted
to
th
e
f
ar
m
er
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8708
A
n
effec
tive
id
en
tifi
ca
tio
n
o
f c
r
o
p
d
is
ea
s
es u
s
in
g
fa
s
ter r
eg
io
n
b
a
s
ed
c
o
n
vo
lu
tio
n
a
l n
e
u
r
a
l
.
..
(
P
.
C
h
a
n
d
a
n
a
)
6539
6.
CO
M
P
ARATI
VE
S
T
UDY
T
h
e
P
r
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p
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s
ed
m
eth
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d
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lo
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s
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th
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d
ata
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o
f
m
aize
cr
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d
co
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t
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t
d
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o
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ith
m
s
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ased
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r
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r
k
(
R
-
C
N
N)
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Fas
t
R
-
C
NN,
Sp
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m
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g
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r
k
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o
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m
s
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h
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co
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
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8
8
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8708
I
n
t J
E
lec
&
C
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m
p
E
n
g
,
Vo
l.
10
,
No
.
6
,
Decem
b
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2020
:
6
5
3
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6
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0
6540
RE
F
E
R
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NC
E
S
[1
]
C.
F
.
T
a
n
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h
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a
p
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m
:
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.
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[3
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S.
S
a
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[4
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.
Ba
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.
[5
]
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N.
Ka
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Co
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.
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S
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.
Ki
m
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[8
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S.
A
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[9
]
H.
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t
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l
.
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ter
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0
]
K.
Jh
a
,
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t
a
l.
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c
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telli
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fi
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In
telli
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in
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g
ric
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lt
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re
,
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l.
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.
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0
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1
]
S
.
A
.
A
l
v
i,
e
t
a
l.
,
“
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tern
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t
o
f
m
u
lt
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e
d
ia
th
in
g
s:
V
isio
n
a
n
d
c
h
a
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len
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s
,”
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Ho
c
N
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two
rk
s
,
v
o
l.
33
,
p
p
.
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-
1
1
1
,
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0
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5
.
[1
2
]
X
.
Ca
o
,
e
t
a
l.
,
“
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g
io
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a
se
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ris
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ield
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t
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so
rs
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l.
1
8
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n
o
.
3
,
p.
7
3
7
,
2
0
1
8
.
[1
3
]
S.
Jin
,
e
t
a
l.
,
“
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e
p
lea
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n
g
:
in
d
iv
id
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a
l
m
a
ize
se
g
m
e
n
tatio
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f
ro
m
terr
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strial
li
d
a
r
d
a
ta
u
sin
g
f
a
s
ter
R
-
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N
a
n
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re
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io
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l
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ro
w
th
a
lg
o
rit
h
m
s,”
Fro
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rs
in
p
la
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e
,
v
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l
.
9
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p
.
8
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6
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0
1
8
.
[1
4
]
P.
Ya
d
a
v
a
n
d
M
.
Ku
m
a
ri
,
“
Ob
jec
t
Re
c
o
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n
it
io
n
Us
in
g
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e
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a
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n
Io
T
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p
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c
a
ti
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n
s
,”
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n
Pro
c
e
e
d
in
g
s
o
f
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r
d
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ter
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io
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l
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fer
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ter
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T
h
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g
s
a
n
d
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o
n
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e
c
ted
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e
c
h
n
o
lo
g
ies
(
ICIo
T
CT
)
,
2
0
1
8
.
[1
5
]
C.
L
o
p
e
z
-
Ca
sta
ñ
o
,
e
t
a
l.
,
“
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m
p
u
ter
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a
n
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th
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tern
e
t
o
f
th
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o
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ste
m
in
th
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ted
h
o
m
e
,”
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n
In
ter
n
a
t
io
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a
l
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y
mp
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si
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m o
n
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ib
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te
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m
p
u
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a
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d
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fi
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telli
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e
,
p
p
.
2
1
3
-
2
2
0
,
2
0
1
8
.
[1
6
]
M
.
F
.
R
u
to
lo
,
e
t
a
l.
,
“
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h
e
u
se
o
f
a
n
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tro
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e
a
rl
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sig
n
s
o
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so
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t
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ro
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p
o
tat
o
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s
,”
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o
sy
ste
ms
e
n
g
in
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e
rin
g
,
v
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l
.
1
6
7
,
p
p
.
1
3
7
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1
4
3
,
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0
1
8
.
[1
7
]
U.
S
h
r
u
th
i
,
e
t
a
l.
,
“
A
Re
v
i
e
w
o
n
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a
c
h
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e
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rn
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g
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sif
ica
ti
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n
T
e
c
h
n
iq
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e
s
f
o
r
P
lan
t
Dise
a
se
De
tec
ti
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n
,”
i
n
2
0
1
9
5
th
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Ad
v
a
n
c
e
d
Co
mp
u
ti
n
g
&
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mm
u
n
ica
ti
o
n
S
y
ste
ms
(
ICACCS
)
,
p
p
.
2
8
1
-
2
8
4
,
2
0
1
9
.
[1
8
]
J.
G
a
o
,
e
t
a
l.
,
“
Re
c
o
g
n
isin
g
w
e
e
d
s
in
a
m
a
ize
c
ro
p
u
sin
g
a
ra
n
d
o
m
f
o
re
st
m
a
c
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lea
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g
a
lg
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rit
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m
a
n
d
n
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a
r
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in
f
ra
re
d
sn
a
p
sh
o
t
m
o
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ic h
y
p
e
rsp
e
c
tral
ima
g
e
r
y
,”
Bi
o
sy
ste
ms
En
g
in
e
e
rin
g
,
v
o
l.
1
7
0
,
p
p
.
39
-
50
,
2
0
1
8
.
[1
9
]
K.
G
.
L
ia
k
o
s,
e
t
a
l.
,
“
M
a
c
h
in
e
le
a
rn
in
g
i
n
a
g
ricu
lt
u
re
:
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re
v
ie
w
,”
S
e
n
so
rs
,
v
o
l.
1
8
,
n
o
.
8
,
p
.
2
6
7
4
-
2
7
0
2
,
2
0
1
8
.
[2
0
]
K.
S
e
k
a
ra
n
,
et
a
l.
,
“
De
e
p
lea
r
n
in
g
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o
n
v
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l
u
ti
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l
n
e
u
ra
l
n
e
two
rk
(CNN
)
W
it
h
G
a
u
ss
ian
m
i
x
tu
re
m
o
d
e
l
f
o
r
p
re
d
ictin
g
p
a
n
c
re
a
ti
c
c
a
n
c
e
r
,
”
M
u
lt
ime
d
ia
T
o
o
ls a
n
d
Ap
p
li
c
a
ti
o
n
s
,
v
o
l.
7
9
,
pp.
1
0
2
3
3
-
1
0
2
4
7
,
20
20
.
[2
1
]
M
.
A
.
Hu
ss
e
in
a
n
d
A
.
H.
A
b
b
a
s
,
“
P
lan
t
L
e
a
f
Dise
a
se
D
e
tec
ti
o
n
Us
in
g
S
u
p
p
o
rt
V
e
c
to
r
M
a
c
h
in
e
,”
Al
-
M
u
sta
n
siriy
a
h
J
o
u
rn
a
l
o
f
S
c
ien
c
e
,
v
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l
.
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0
,
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o
.
1
,
p
p
.
1
0
5
-
1
1
0
,
2
0
1
9
.
[2
2
]
K
.
S
e
k
a
ra
n
,
e
t
a
l.
,
“
S
m
a
rt
a
g
ricu
lt
u
re
m
a
n
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g
e
m
e
n
t
s
y
ste
m
u
sin
g
in
tern
e
t
o
f
th
in
g
s
,”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ica
ti
o
n
Co
mp
u
ti
n
g
E
lec
tro
n
ics
a
n
d
C
o
n
tr
o
l
,
v
ol
.
1
8
,
n
o
.
3
,
p
p
.
1
2
7
5
-
1
2
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4
,
2
0
2
0
.
[2
3
]
K
.
S
e
k
a
ra
n
,
e
t
a
l.
,
“
De
sig
n
o
f
o
p
ti
m
a
l
se
a
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h
e
n
g
in
e
u
sin
g
tex
t
su
m
m
a
riz
a
ti
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n
th
r
o
u
g
h
a
rt
if
icia
l
in
telli
g
e
n
c
e
tec
h
n
i
q
u
e
s
,”
T
E
L
KOM
NIKA
T
e
lec
o
mm
u
n
ica
ti
o
n
Co
m
p
u
ti
n
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l
,
v
ol
.
1
8
,
n
o
.
3
,
p
p
.
1
2
6
8
-
1
2
7
4
,
2
0
2
0
.
[2
4
]
B.
V
ij
a
y
a
la
x
m
i,
e
t
a
l.
,
“
I
m
p
le
m
e
n
tatio
n
o
f
f
a
c
e
a
n
d
e
y
e
d
e
te
c
ti
o
n
o
n
DM
6
4
3
7
b
o
a
rd
u
si
n
g
sim
u
li
n
k
m
o
d
e
l
,”
Bu
ll
e
ti
n
o
f
El
e
c
trica
l
E
n
g
in
e
e
rin
g
a
n
d
I
n
fo
rm
a
t
ics
(
BE
EI)
,
v
o
l.
9
,
n
o
.
2
,
p
p
.
7
8
5
-
7
9
1
,
2
0
2
0
.
[2
5
]
B.
V
ij
a
y
a
la
x
m
i,
e
t
a
l.
,
“
I
m
a
g
e
p
r
o
c
e
ss
in
g
-
b
a
se
d
e
y
e
d
e
tec
ti
on
m
e
th
o
d
s
a
th
e
o
re
ti
c
a
l
re
v
ie
w
,”
Bu
ll
e
ti
n
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
I
n
fo
rm
a
ti
c
s
(
BE
EI)
,
v
o
l.
9
,
n
o
.
3
,
p
p
.
1
1
8
9
-
1
1
9
7
,
2
0
2
0
.
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