Optimizing Object Detection Accuracy and Computational Efficiency Using GLCM-Based Feature Combinations and Machine Learning Models

This research aims to enhance computational efficiency in object detection by selecting appropriate feature combinations within the GLCM framework and evaluating the performance of K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) classification models.