Enhancing early detection of Alzheimer’s disease through hybrid models based on feature fusion of multi-CNN and handcrafted features
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Dec. 28, 2024
Language: Английский
BiFPN-enhanced SwinDAT-based cherry variety classification with YOLOv8
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Feb. 13, 2025
Accurate
classification
of
cherry
varieties
is
crucial
for
their
economic
value
and
market
differentiation,
yet
genetic
diversity
visual
similarity
make
manual
identification
challenging,
hindering
efficient
agricultural
trade
practices.
This
study
addresses
this
issue
by
proposing
a
novel
deep
learning-based
hybrid
model
that
integrates
BiFPN
with
the
YOLOv8n-cls
framework,
enhanced
Swin
Transformer
Deformable
Attention
(DAT)
techniques.
The
was
trained
evaluated
on
newly
constructed
dataset
comprising
from
Turkey's
Western
Mediterranean
region.
Experimental
results
demonstrated
effectiveness
proposed
approach,
achieving
precision
91.91%,
recall
92.0%,
F1-score
91.93%,
an
overall
accuracy
91.714%.
findings
highlight
model's
potential
to
optimize
harvest
timing,
ensure
quality
control,
support
export
classification,
thereby
contributing
improved
practices
outcomes.
Language: Английский
Analysis of Machine Learning Algorithms for Real-Time Gallbladder Stone Identification from Ultrasound Images in Clinical Decision Support Systems
International Journal of Computational Intelligence Systems,
Journal Year:
2025,
Volume and Issue:
18(1)
Published: April 2, 2025
Language: Английский