Multi-scale spatial pyramid attention mechanism for image recognition: An effective approach
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
133, С. 108261 - 108261
Опубликована: Апрель 5, 2024
Язык: Английский
Automated pixel-level pavement marking detection based on a convolutional transformer
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
133, С. 108416 - 108416
Опубликована: Апрель 25, 2024
Язык: Английский
Development of optimized ensemble machine learning-based character segmentation framework for ancient Tamil palm leaf manuscripts
Engineering Applications of Artificial Intelligence,
Год журнала:
2025,
Номер
146, С. 110235 - 110235
Опубликована: Фев. 20, 2025
Язык: Английский
Self-supervised multi-modality learning for multi-label skin lesion classification
Computer Methods and Programs in Biomedicine,
Год журнала:
2025,
Номер
unknown, С. 108729 - 108729
Опубликована: Апрель 1, 2025
Язык: Английский
Artificial intelligence for computer aided detection of pneumoconiosis: A succinct review since 1974
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
133, С. 108516 - 108516
Опубликована: Май 2, 2024
Язык: Английский
Diverter transformer-based multi-encoder-multi-decoder network model for medical retinal blood vessel image segmentation
Biomedical Signal Processing and Control,
Год журнала:
2024,
Номер
93, С. 106132 - 106132
Опубликована: Фев. 23, 2024
Язык: Английский
Efficient Feature Extraction and Segmentation Methods Used in Tuberculosis Detection
Emil. M. Paul,
G. Jayahari Prabhu,
B. Perumal
и другие.
2021 International Conference on Emerging Smart Computing and Informatics (ESCI),
Год журнала:
2024,
Номер
unknown, С. 1 - 5
Опубликована: Март 5, 2024
According
to
X-ray
images,
the
segmentation
and
classification
with
noise
removal
are
major
stages.
When
seen
from
different
perspectives
or
in
various
lighting
conditions,
chest
image
appears
differently.
This
paper
discusses
threat
that
tuberculosis
poses
across
globe.
Although
there
many
medical
treatments
available,
TB
diagnosis
is
still
challenging.
Several
clinical
diagnostic
processes
earlier
poster
anterior
radiographs
contain
computationally
developed
algorithms
simplify
scientific
analysis
by
utilizing
acquisition.
It
possible
a
digital
will
be
required
for
annotation
of
patient's
demographic
information
while
being
screened
via
radiography.
Special
screening
victimization.
work
proposed
novel
detection
model
tuberculosis.
Initially,
analyzed
input
noises
after
median
filter
performing
pre-processing
followed
watershed
mechanism
segmentation.
Next,
feature
extraction
carried
out
GLCM
support
vector
machine
(SVM)
classifying
normal
The
Kaggle
dataset
MATLAB
software
handled
implementation
part
it
describes
performances
higher
than
existing
works.
Язык: Английский
Advancing Chest X-ray Diagnostics via Multi-Modal Neural Networks with Attention
Опубликована: Июль 15, 2024
The
healthcare
field
is
undergoing
a
profound
shift,
with
deep
learning
in
AI
increasingly
augmenting
medical
expertise
complex
and
challenging
tasks.
Our
research
addresses
the
task
of
chest
X-ray
image
diagnostics,
characterized
by
multifaceted
diagnostic
labels
class
im-balances
respiratory
disease
cases.
approach
synergizes
pre-trained
classification
neural
network
patient
metadata
integration,
significantly
boosting
precision.
A
key
aspect
our
methodology
identification
an
effective
decision
boundary
to
enhance
accuracy
reduce
false
positives.
effectiveness
model
demonstrated
average
AUC
score
0.84,
surpassing
existing
models
signifying
notable
leap
AI's
role
diagnostics.
This
tool
stands
aid
clinical
decision-making,
particularly
navigating
complexities
comorbidities
health.
Язык: Английский