<![CDATA[Flowers are transformations of buds, including stems and leaves, with shapes and colors adapted to the plant's functions. They also serve as sites for fertilization and pollination. Flowers come in various shapes and colors, with over 250,000 flowering plant species known and classified into 350 families. Therefore, employing technology for flower pattern recognition is crucial for enhancing accuracy and efficiency. One effective method involves using Artificial Neural Networks (ANN) in conjunction with the perceptron algorithm. This algorithm has proven effective in image-based pattern recognition due to its ability to learn complex and linear patterns from image data. This study explores the use of neural networks, specifically the perceptron method, in recognizing flower patterns. The test utilizes sunflower image samples, with the perceptron algorithm applied to produce accurate and effective data in flower pattern recognition.]]>
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