CNN-Based Image Classification for Face-Spoof Detection Using AI and ML

With the rapid development of digital content identification in recent years, automatic image classification has become the most difficult task in computer vision. Compared to human vision, it is challenging for systems to comprehend and analyze images automatically. A few examinations have been finished to conquer issues in the existing grouping framework; however, the result was restricted exclusively to low even-out picture natives. However, these methods fail to classify images accurately. Our system employs a machine learning algorithm in this paper to produce the anticipated outcomes in computer visions. We achieved an experimental accuracy of 97.5% for grayscale image classification, demonstrating that our model can accurately classify images.