Performance metric of optimized CNN with Adam for <i>β</i> = 1 .

Performance metric of optimized CNN with Adam for <i>β</i> = 1 .

<p>Performance metric of optimized CNN with Adam for <i>β</i> = 1 .</p>

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Bibliographic Details
Main Author: Ali Raza (3558965) (author)
Other Authors: Akhtar Ali (603199) (author), Sami Ullah (613609) (author), Yasir Nadeem Anjum (20934626) (author), Basit Rehman (20934629) (author)
Published: 2025
Subjects:
Medicine
Immunology
Developmental Biology
Cancer
Science Policy
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
smart healthcare application
mathematical computational cost
healthcare providers diagnosing
convolutional neural networks
evaluate model interpretability
skin cancer classification
cancer skin classification
div >< p
cross validation technique
classification accuracy rates
>) could lead
skin cancer class
model training involved
develop reliable optimized
skin cancer
model ’
skin lesions
healthy class
xai </
would assist
unseen data
unseed data
turn leads
strongly associated
skin disease
seven forms
rmsprop </
prevalent types
prediction models
patient ’
optimized cnn
offered specifically
network fitting
much smaller
key aspect
interpretational aspects
initial diagnosis
holdout validation
healthare expenditure
ham10000 </
generalization performance
generalization ability
enhanced speed
early detection
drawbacks mainly
detected early
convergence rate
cnn </
clinical examination
central component
cam </
cam ++</
better performance
better outcomes
algorithms applied
af </
adam </
activation functions
>, achieving
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