Image Classification Using Python and Techniques of Computer Vision and Machine Learning

This book implemented six different algorithms to classify images with prediction accuracy as the primary criterion and time consumption as the secondary one. The accuracies varied between about 30% and 90%, while the time consumptions varied from several seconds to more than one hour. Considering both criteria, the Pre-Trained AlexNet Features Representation plus a Classifier, such as the k-Nearest Neighbors (KNN) and the Support Vector Machines (SVM), was concluded as the best algorithm.