Journal of Optics,
Journal Year:
2024,
Volume and Issue:
26(6), P. 065402 - 065402
Published: April 25, 2024
Abstract
Vectorial
adaptive
optics
(V-AO)
is
a
cutting-edge
technique
extending
conventional
AO
into
the
vectorial
domain
encompassing
both
polarization
and
phase
feedback
correction
for
optical
systems.
However,
previous
V-AO
approaches
focus
on
point
correction.
In
this
letter,
we
extend
approach
imaging
domain.
We
show
how
can
benefit
an
aberrated
system
to
enhance
not
only
scalar
but
also
quality
of
information.
Two
important
criteria,
precision
uniformity
are
put
forward
used
in
practice
evaluate
performance
These
experimental
validations
pave
way
real-world
technology
its
applications.
Journal of Personalized Medicine,
Journal Year:
2023,
Volume and Issue:
13(2), P. 181 - 181
Published: Jan. 20, 2023
The
field
of
medical
image
processing
plays
a
significant
role
in
brain
tumor
classification.
survival
rate
patients
can
be
increased
by
diagnosing
the
at
an
early
stage.
Several
automatic
systems
have
been
developed
to
perform
recognition
process.
However,
existing
could
more
efficient
identifying
exact
region
and
hidden
edge
details
with
minimum
computation
complexity.
Harris
Hawks
optimized
convolution
network
(HHOCNN)
is
used
this
work
resolve
these
issues.
magnetic
resonance
(MR)
images
are
pre-processed,
noisy
pixels
eliminated
minimize
false
rate.
Then,
candidate
process
applied
identify
region.
method
investigates
boundary
regions
help
line
segments
concept,
which
reduces
loss
details.
Various
features
extracted
from
segmented
region,
classified
applying
convolutional
neural
(CNN).
CNN
computes
fault
tolerance.
proposed
HHOCNN
system
was
implemented
using
MATLAB,
performance
evaluated
pixel
accuracy,
error
rate,
specificity,
sensitivity
metrics.
nature-inspired
optimization
algorithm
minimizes
misclassification
improves
overall
accuracy
98%
achieved
on
Kaggle
dataset.
Energy Strategy Reviews,
Journal Year:
2024,
Volume and Issue:
53, P. 101409 - 101409
Published: May 1, 2024
The
synergy
between
deep
learning
and
meta-heuristic
algorithms
presents
a
promising
avenue
for
tackling
the
complexities
of
energy-related
modeling
forecasting
tasks.
While
excels
in
capturing
intricate
patterns
data,
it
may
falter
achieving
optimality
due
to
nonlinear
nature
energy
data.
Conversely,
offer
optimization
capabilities
but
suffer
from
computational
burdens,
especially
with
high-dimensional
This
paper
provides
comprehensive
review
spanning
2018
2023,
examining
integration
within
frameworks
applications.
We
analyze
state-of-the-art
techniques,
innovations,
recent
advancements,
identifying
open
research
challenges.
Additionally,
we
propose
novel
framework
that
seamlessly
merges
into
paradigms,
aiming
enhance
performance
efficiency
addressing
problems.
contributions
include:
1.
Overview
advancements
MHs,
DL,
integration.
2.
Coverage
trends
2023.
3.
Introduction
Alpha
metric
evaluation.
4.
Innovative
harmonizing
MHs
DL
Biomimetics,
Journal Year:
2023,
Volume and Issue:
8(3), P. 278 - 278
Published: June 28, 2023
The
application
of
artificial
intelligence
in
everyday
life
is
becoming
all-pervasive
and
unavoidable.
Within
that
vast
field,
a
special
place
belongs
to
biomimetic/bio-inspired
algorithms
for
multiparameter
optimization,
which
find
their
use
large
number
areas.
Novel
methods
advances
are
being
published
at
an
accelerated
pace.
Because
that,
spite
the
fact
there
lot
surveys
reviews
they
quickly
become
dated.
Thus,
it
importance
keep
pace
with
current
developments.
In
this
review,
we
first
consider
possible
classification
bio-inspired
optimization
because
papers
dedicated
area
relatively
scarce
often
contradictory.
We
proceed
by
describing
some
detail
more
prominent
approaches,
as
well
those
most
recently
published.
Finally,
biomimetic
two
related
wide
fields,
namely
microelectronics
(including
circuit
design
optimization)
nanophotonics
inverse
structures
such
photonic
crystals,
nanoplasmonic
configurations
metamaterials).
attempted
broad
survey
self-contained
so
can
be
not
only
scholars
but
also
all
interested
latest
developments
attractive
area.
