Muhammad Attique Khan1, Abdul Majid1, Nazar Hussain1, Majed Alhaisoni2, Yu-Dong Zhang3, Seifedine Kadry4, Yunyoung Nam5,*
CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3381-3399, 2021, DOI:10.32604/cmc.2021.014983
Abstract In the area of medical image processing, stomach cancer is one of the most important cancers which need to be diagnose at the early stage. In this paper, an optimized deep learning method is presented for multiple stomach disease classification. The proposed method work in few important steps—preprocessing using the fusion of filtering images along with Ant Colony Optimization (ACO), deep transfer learning-based features extraction, optimization of deep extracted features using nature-inspired algorithms, and finally fusion of optimal vectors and classification using Multi-Layered Perceptron Neural Network (MLNN). In the feature extraction step, pre-trained Inception V3 is utilized and retrained on… More >
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