Implementation of a Convolutional Neural Network for Binary Image Classification Using Tensor Flow

This paper presents the design and implementation of a simple Convolutional Neural Network (CNN) using Tensor Flow for binary image classification. The proposed model classifies 5×5 pixel images into two categories: images containing the pattern of an 'X' and images that do not. The study demonstrates dataset generation, model architecture, training, and evaluation, highlighting the effectiveness of CNNs for pattern recognition tasks.