2019 Innovations in Power and Advanced Computing Technologies (i-PACT),
Journal Year:
2023,
Volume and Issue:
unknown, P. 1 - 6
Published: Dec. 8, 2023
Yoga
is
a
popular
practice
that
aims
to
improve
one's
health
and
well-being
through
physical
postures,
breathing
exercises,
meditation.
The
growing
popularity
of
yoga
has
prompted
researchers
focus
on
automating
the
process
classifying
poses.
Using
deep
convolutional
neural
networks
(CNNs)
transfer
learning,
we
present
learning-based
method
for
correctly
categorizing
postures
in
this
research.
primary
goal
study
develop
an
efficient
automatically
recognizing
poses
given
photographs.
impressive
success
CNNs
picture
classification
tasks
exploited
here
accomplish
goal.
We
also
use
customizing
pre-trained
CNN
models
our
unique
posture
categorization
task.
This
paper
presents
Transfer
Learning
based
Method
Poses
using
Deep
Convolutional
Neural
Networks
(TLMYPC-DCNN).
proposed
model
uses
Posture
Dataset
images.
Initially,
starts
with
pre-processing
input
images
by
splitting
data
into
three
groups
such
as
training
set,
validation
set
test
data.
learning
will
be
trained
data,
then
its
parameters
tweaked
Finally,
used
assess
how
well
performs.
A
network
(CNN)
called
MobileNetV2
applied
photos.
experimental
results
show
suggested
TLMYPC-DCNN
technique
effective
at
accurately
reliably
SN Computer Science,
Journal Year:
2023,
Volume and Issue:
4(2)
Published: Feb. 8, 2023
Yoga
has
become
an
integral
part
of
human
life
to
maintain
a
healthy
body
and
mind
in
recent
times.
With
the
growing,
fast-paced
work
from
home,
it
difficult
for
people
invest
time
gymnasium
exercises.
Instead,
they
like
do
assisted
exercises
at
home
where
pose
recognition
techniques
play
most
vital
role.
Recognition
different
poses
is
challenging
due
proper
dataset
classification
architecture.
In
this
work,
we
have
proposed
deep
learning-based
model
identify
five
yoga
comparatively
fewer
amounts
data.
We
compared
our
model's
performance
with
some
state-of-the-art
image
models-ResNet,
InceptionNet,
InceptionResNet,
Xception
found
architecture
superior.
Our
extracts
spatial,
depth
features
individually
considers
them
further
calculation
classification.
The
experimental
results
show
that
achieved
94.91%
accuracy
95.61%
precision.
Bioengineering,
Journal Year:
2023,
Volume and Issue:
10(4), P. 459 - 459
Published: April 9, 2023
The
physical
and
mental
health
of
people
can
be
enhanced
through
yoga,
an
excellent
form
exercise.
As
part
the
breathing
procedure,
yoga
involves
stretching
body
organs.
guidance
monitoring
are
crucial
to
ripe
full
benefits
it,
as
wrong
postures
possess
multiple
antagonistic
effects,
including
hazards
stroke.
detection
possible
with
Intelligent
Internet
Things
(IIoT),
which
is
integration
intelligent
approaches
(machine
learning)
(IoT).
Considering
increment
in
practitioners
recent
years,
IIoT
has
led
successful
implementation
IIoT-based
training
systems.
This
paper
provides
a
comprehensive
survey
on
integrating
IIoT.
also
discusses
types
procedure
for
using
Additionally,
this
highlights
various
applications
safety
measures,
challenges,
future
directions.
latest
developments
findings
its
Journal of Healthcare Engineering,
Journal Year:
2023,
Volume and Issue:
2023, P. 1 - 13
Published: Jan. 1, 2023
In
conventional
healthcare,
real-time
monitoring
of
patient
records
and
information
mining
for
timely
diagnosis
chronic
diseases
under
certain
health
conditions
is
a
crucial
process.
Chronic
diseases,
if
not
diagnosed
in
time,
may
result
patients’
death.
modern
medical
healthcare
systems,
Internet
Things
(IoT)
driven
ecosystems
use
autonomous
sensors
to
sense
track
suggest
appropriate
actions.
this
paper,
novel
IoT
machine
learning
(ML)-based
hybrid
approach
proposed
that
considers
multiple
perspectives
early
detection
6
different
such
as
COVID-19,
pneumonia,
diabetes,
heart
disease,
brain
tumor,
Alzheimer’s.
The
results
from
ML
models
are
compared
accuracy,
precision,
recall,
F1
score,
area
the
curve
(AUC)
performance
measure.
validated
cloud-based
environment
using
benchmark
real-world
datasets.
statistical
analyses
on
datasets
ANOVA
tests
show
accuracy
classifiers
significantly
different.
This
will
help
sector
doctors
diseases.
Advances in Complex Systems,
Journal Year:
2023,
Volume and Issue:
15(02)
Published: April 5, 2023
Breast
cancer
(BC)
is
one
of
the
major
principal
sources
high
mortality
among
women
worldwide.
Consequently,
early
detection
essential
to
save
lives.
BC
can
be
diagnosed
with
different
modes
medical
images
such
as
mammography,
ultrasound,
computerized
tomography,
biopsy,
and
magnetic
resonance
imaging.
A
histopathology
study
(biopsy)
that
results
in
often
performed
help
diagnose
analyze
BC.
Transfer
learning
(TL)
a
machine-learning
(ML)
technique
reuses
method
initially
built
for
task
applied
model
new
task.
TL
aims
enhance
assessment
desired
learners
by
moving
knowledge
contained
another
but
similar
source
domain.
challenge
small
dataset
domain
reduced
build
learners.
plays
role
image
analysis
because
this
immense
property.
This
paper
focuses
on
use
methods
investigation
classification
detection,
preprocessing,
pretrained
models,
ML
models.
Through
empirical
experiments,
EfficientNets
neural
network
architectures
models
were
built.
The
support
vector
machine
eXtreme
Gradient
Boosting
(XGBoost)
learned
dataset.
result
showed
comparative
good
performance
EfficientNetB4
XGBoost.
An
outcome
based
accuracy,
recall,
precision,
F1_Score
XGBoost
84%,
0.80,
0.83,
0.81,
respectively.
Hydrogen,
Journal Year:
2024,
Volume and Issue:
5(4), P. 819 - 850
Published: Nov. 10, 2024
This
study
addresses
the
growing
need
for
effective
energy
management
solutions
in
university
settings,
with
particular
emphasis
on
solar–hydrogen
systems.
The
study’s
purpose
is
to
explore
integration
of
deep
learning
models,
specifically
MobileNetV2
and
InceptionV3,
enhancing
fault
detection
capabilities
AIoT-based
environments,
while
also
customizing
ISO
50001:2018
standards
align
unique
needs
academic
institutions.
Our
research
employs
comparative
analysis
two
models
terms
their
performance
detecting
solar
panel
defects
assessing
accuracy,
loss
values,
computational
efficiency.
findings
reveal
that
achieves
80%
making
it
suitable
resource-constrained
InceptionV3
demonstrates
superior
accuracy
90%
but
requires
more
resources.
concludes
both
offer
distinct
advantages
based
application
scenarios,
emphasizing
importance
balancing
efficiency
when
selecting
appropriate
system
management.
highlights
critical
role
continuous
improvement
leadership
commitment
successful
implementation
universities.
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT),
Journal Year:
2023,
Volume and Issue:
unknown
Published: July 6, 2023
Identifying
human
actions
and
postures
presents
significant
challenges
for
computerized
systems.
The
categorization
of
these
tasks
holds
particular
relevance
in
the
fields
health
robotics.
Leveraging
artificial
intelligence
technologies,
it
becomes
feasible
to
define
classify
recurring
physical
movements
accurately.
Proper
posture
is
further
essential
rehabilitation
patients
because
affects
effectiveness
exercise
training.
Unfortunately,
fail
follow
correct
sequence
when
performing
exercises.
To
pursue
problem,
a
new
method
proposed
recognition
pose
estimation
that
does
not
require
wearable
devices.
model
utilizes
2D
coordinates
derived
from
poses
as
inputs
with
18
joints
body
key
points,
along
an
image
dataset,
accurately
various
postures.
This
study
involved
training
custom
CNN
named
DeepPose
using
both
keypoint
datasets
conducting
comparative
analysis
performance
two
other
pre-trained
models.
result
shows
dataset
outperforms
over
dataset.