Table 4 Experimental Parameters for Proposed Model.

From: A precise model for skin cancer diagnosis using hybrid U-Net and improved MobileNet-V3 with hyperparameters optimization

Parameters

Details

Batch size

8

Data augmentation strategies

Flipping, zooming, translations and rotations,

Normalization

0, 1

Regularization

L2 regularization (Weight decay)

Optimizer

‘Adam optimizer’

Dropout rate

0.1

Epochs

100

Image input size

(224 × 224)

Hyperparameter optimization

Bayesian optimization

Transfer learning

MobileNet-V3

Loss function

Multi-class categorical cross-entropy function

Learning rate

0.2

Growth rate

24

Split ratio

Training: testing: validation 70: 15: 15

Shuffling in database

“YES”

Brightness range

[0.2, 2.25]

Rotation

0 to 15 Degrees