CNN for bacteria and archaea classification using FCGR images

Prokaryotes, which comprise both bacteria and archaea, are found everywhere around us. Their detecting, counting, and classification is still a hard matter. This paper's main aim is the prokaryotes classification using the frequency chaos representation (FCGR) image and convolutional neural networks (CNN). First, we mapped each bacteria and archaebacterial DNA sequence by using the FCGR images with different orders. Next, we apply a binary classification using the CNN technique. Our model has shown a precision that exceeds 92%. This result shows the proposed method's performance.