Using a PMCN-PSA, image classification tasks will be carried out in this research. Since Tensorflow is a Python library, Python will be our primary programming language in this case. The majority of the input data used in the research focuses on plant classification using leaf types. The best course of action for the training and testing data is to use PMCN-PSA because it consistently produces positive outcomes for automated plant identifications. TensorFlow's performance analysis for the precision of the model's prediction on TensorFlow and a comparison of the outcomes with Python show that the model can predict outcomes effectively and accurately when compared to both human cognition and computational neural networks in terms of image recognition. On the Intel® CoreTM i3-7100U CPU, TensorFlow with nonlinearity demonstrated remarkable accuracy at 95%.