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. Read More
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. Read Less
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Add this copy of Image Classification Using Python and Techniques of to cart. $73.66, good condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Santa Clarita, CA, UNITED STATES, published 2019 by Independently published.
