Abstract: Early detection of plant diseases is essential for safeguarding crop health and enhancing agricultural productivity. Traditional methods relying on manual observation are often slow, inaccurate, and inefficient. This ponder proposes a unused approach utilizing Convolutional Neural Systems (CNNs) to consequently distinguish plant maladies, altogether upgrading speed and precision. The show is prepared on a comprehensive collection of pictures, covering both solid and infected plant clears out, driving to a tall discovery rate. By joining exchange learning, the framework can perform successfully indeed with constrained information. Planned to function in real-time and at scale, this device is available to agriculturists, advertising a viable arrangement that diminishes the require for pesticides, bolsters way better trim administration, and empowers more feasible rural hones.
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DOI:
10.17148/IJARCCE.2025.14410
