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Early detection of tomato leaf diseases is critical to prevent their spread, but manual detection methods for the same are time-consuming, inconsistent, and labor-intensive. To address this problem, researchers from China developed a novel deep learning network architecture called PLPNet that can accurately detect and distinguish different leaf diseases in real time. Their approach effectively addresses the limitations of previous models and paves the way to smarter agricultural practices.