1 publication

• Published Subscription 22 Nov 2023

  Support Vector Machine-based Flower Image Classification for Commercial Applications

  By Shubham Sarvade, Sneha Mhatre, Aditi Sawant, Babeetta Bbhagat

  Abstract: Flowers are crucial raw materials in many industries, including pharmaceuticals and cosmetics. Classifying flowers manually is time-consuming, inconsistent, and requires professional judgment from a botanist. Computer-aided flower classification is a promising approach to this problem. Image classification often employs support vector machines (SVMs) as widely favored algorithms. This study evaluated the performance of SVMs for flower image classification. The results showed that SVMs can achieve good accuracy on this task, …

  Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 44–53 Read article →