Drones,
Год журнала:
2024,
Номер
8(8), С. 385 - 385
Опубликована: Авг. 8, 2024
Long-endurance
unmanned
aerial
vehicles
(LE-UAVs)
are
extensively
used
due
to
their
vast
coverage
and
significant
payload
capacities.
However,
limited
autonomous
intelligence
necessitates
the
intervention
of
ground
control
resources
(GCRs),
which
include
one
or
more
operators,
during
mission
execution.
The
performance
these
missions
is
notably
affected
by
varying
effectiveness
different
GCRs
fatigue
levels.
Current
research
on
multi-UAV
planning
inadequately
addresses
critical
factors.
To
tackle
this
practical
issue,
we
present
an
integrated
optimization
problem
for
multi-LE-UAV
combined
with
heterogeneous
GCR
allocation.
This
extends
traditional
cooperative
incorporating
allocation
decisions.
coupling
decisions
increases
dimensionality
decision
space,
rendering
complex.
By
analyzing
problem’s
characteristics,
develop
a
mixed-integer
linear
programming
model.
effectively
solve
problem,
propose
bilevel
algorithm
based
hybrid
genetic
framework.
Numerical
experiments
demonstrate
that
our
proposed
solves
outperforming
advanced
toolkit
CPLEX.
Remarkably,
larger-scale
instances,
achieves
superior
solutions
within
10
s
compared
CPLEX’s
2
h
runtime.
Remote Sensing,
Год журнала:
2025,
Номер
17(9), С. 1647 - 1647
Опубликована: Май 7, 2025
Beachrocks
are
common
coastal
sedimentary
rocks
in
tropical
and
subtropical
seas.
They
widely
spread
especially
islands
areas.
These
important
for
island
geological
evolution
research.
Research
on
beachrocks
aids
protecting
ecosystems
enhances
islands’
ability
to
prevent
mitigate
damage
from
natural
disasters.
This
study
uses
unmanned
aerial
vehicle
(UAV)
images
the
U-Net
model
based
deep
learning
identify
beachrocks.
To
enhance
identification
accuracy,
efficient
channel
attention
(ECA)
mechanism
was
integrated,
leading
improvements
of
0.49%
overall
1.41%
precision,
0.97%
recall,
1.10%
F1-score,
2.09%
intersection
over
union
(IoU)
compared
baseline
model.
The
final
results
demonstrate
that
effectively
identified
beachrocks,
achieving
97.47%
93.27%
94.73%
93.95%
88.65%
IoU.
offers
a
valuable
tool
research
supports
development
large-scale
conservation
efforts.
Geomechanics and Tunnelling,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 20, 2025
Abstract
Remote
sensing
technologies
have
significantly
transformed
engineering
geology
over
the
past
two
decades,
enabling
efficient
data
collection
for
infrastructure
inspection
and
site
characterization.
Advances
in
sensor
platforms,
including
unmanned
aerial
vehicle
(UAV)‐based
photogrammetry,
light
detection
ranging
(LiDAR),
interferometric
synthetic
aperture
radar
(InSAR),
led
to
significant
advances
terrain
monitoring,
rock
mass
characterization,
geohazard
assessment.
While
these
improve
accuracy
accessibility,
they
also
introduce
challenges
related
processing
integration.
This
study
discusses
advantages
limitations
of
active
passive
remote
methods
emphasizes
their
role
geological
investigations.
Based
on
short
case
studies,
need
multidisciplinary
approaches
fully
exploit
geology,
ensuring
more
reliable
cost‐effective
monitoring
hazard
mitigation
strategies.
Earth Science Informatics,
Год журнала:
2024,
Номер
17(5), С. 3963 - 3977
Опубликована: Авг. 9, 2024
Abstract
In
recent
years,
remote
sensing
technologies
have
played
a
crucial
role
in
the
detection
and
management
of
natural
disasters.
this
context,
deep
learning
models
are
great
importance
for
early
disasters
such
as
landslides.
Landslide
segmentation
is
fundamental
tool
development
geographic
information
systems,
disaster
risk
mitigation
strategies.
study,
we
propose
new
semantic
model
called
LandslideSegNet
to
improve
intervention
capabilities
potential
landslide
scenarios.
incorporates
an
encoder-decoder
architecture
that
integrates
local
contextual
information,
advanced
residual
blocks
Efficient
Hybrid
Attentional
Atrous
Convolution.
Thanks
structure,
able
extract
high-resolution
feature
maps
from
imagery,
accurately
delineate
areas
minimize
loss
information.
The
developed
has
shown
significantly
higher
accuracy
rates
with
fewer
parameters
compared
existing
image
models.
was
trained
tested
using
Landslide4Sense
dataset
specially
prepared
detection.
achieved
97.60%
73.65%
mean
Intersection
over
Union
73.65
on
dataset,
demonstrating
its
efficiency.
These
results
indicate
usability
related
applications.
Remote Sensing,
Год журнала:
2024,
Номер
16(16), С. 3096 - 3096
Опубликована: Авг. 22, 2024
This
paper
primarily
studies
the
path
planning
problem
for
UAV
formations
guided
by
semantic
map
information.
Our
aim
is
to
integrate
prior
information
from
maps
provide
initial
on
task
points
formations,
thereby
formation
paths
that
meet
practical
requirements.
Firstly,
a
segmentation
network
model
based
multi-scale
feature
extraction
and
fusion
employed
obtain
aerial
containing
environmental
Secondly,
maps,
three-point
optimization
optimal
trajectory
established,
general
formula
calculating
heading
angle
proposed
approximately
decouple
triangular
equation
of
trajectory.
For
large-scale
points,
an
improved
fuzzy
clustering
algorithm
classify
distance
constraints
clusters,
reducing
computational
scale
single
samples
without
changing
sample
size
improving
allocation
efficiency
model.
Experimental
data
show
cluster
method
using
angle-optimized
achieves
8.6%
improvement
in
total
flight
range
compared
other
algorithms
17.4%
reduction
number
large-angle
turns.
