Skin Lesion Detection Based on a Hybrid Classification and Training
Algorithm Using Swarm Intelligence and Neural Networks
AbstractSkin lesion detection has gained a lot of attention in the last couple
of years due to the spread of skin cancer around the world.
System-assisted design requires training and classification structure
that can only be precise if features are selected appropriately along
with improved segmentation of the lesion. This paper introduces a hybrid
classification and training algorithm architecture that uses machine
learning in all aspects of training and feature selection. The algorithm
has been improved by adding novel behavior of Particles and Moth flames
to be precise on nature. The proposed algorithm uses a multilayer
propagation network for training and classification. The proposed work
has been compared with other state-of-the-art algorithms based on
quantitative parameters. The proposed work shows a significant
improvement in all parameters and aspects.