An Image Classification Method Using Hashing Preprocessing
Sergei Ivanov, Tatiana Victorovna Zudilova, Alexander Ruban, Igor Anantchenko, Lubov Ivanova · 2023
In the study, the authors consider classical classification methods for the applied problem of image recognition. Accuracy, computation time, classifier size, training time for the following methods are considered: “Fully Connected Neural Network”, “Convolutional Neural Network”, “Recurrent Neural Network”, “Decision Tree”, “Gradient Boosted Trees”, “Logistic Regression”, “Markov”, “Naive Bayes”, “Nearest Neighbors”, “Random Forest”, “Support Vector Machine”. A new approach “Neural Network with Hash” is proposed, which represents image preprocessing using polynomial hashing. Collision resolution is performed by a fast method of open addressing. A computer experiment on classification by 10 classes was carried out on a dataset of 600 animal images using the Wolfram mathematical package. For the proposed approach with preprocessing, the results showed the same classification accuracy as the classical methods, and a higher training and computational speed than the “Convolutional Neural Network” and “Recurrent Neural Network”.