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A Novel Liver Image Classification Method Using Perceptual Hash-Based Convolutional Neural Network

In this paper used (CNN) convolutional neural network hybrid model called fused perceptual hash-based CNN (f-ph-CNN) and the dataset.

I want using a hybrid method based on LSTM and optimized SVM for Diagnosis of fatty liver disease using a novel Swarm based Ant lion hybrid metaheuristic algorithm, which combines the characteristics of ant colony optimization (ACO) algorithm and local search algorithms are combined with ant lion optimization (ALO) algorithm to optimize parameters before SVM. With ( ct ) type of dataset and comparing it with previous papers and writing a paper that is similar to the rank of the sent papers

Habilidades: Algoritmo, Machine Learning (ML), Python, Neural Networks, Image Processing

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( 0 comentários ) visakhapatnam, India

ID do Projeto: #28005359

1 freelancer está oferecendo em média ₹5556 para esse trabalho

saranyakuduvan

hai... I saw your paper and description. having small doubt about algorithms. in that paper they used DWT svd for features extraction and cnn for classification. you have mentioned lstm instead of cnn . and also menti Mais

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