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@article{187242,
        author = {Abhishek S. Aahadi},
        title = {AgriScan AI: Plant Disease Detection AI for Farmers},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {5220-5222},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187242},
        abstract = {Agricultural work still drives India's economy, since lots of people make their living growing crops. But spotting crop illnesses early? That’s tough for many growers. Old-school ways usually need specialists, lab access, or waiting until damage shows up clearly - by then it’s often too late, cutting harvests hard. Here’s an idea: use artificial intelligence to catch those problems sooner, applying CNN tech that checks leaf photos to tell what’s wrong. The app runs on phones, letting farmers snap pics of leaves so diseases can be spotted right away. Instead of just raw photos, it cleans up images first using OpenCV tools before analysis. It learns from plant sickness data pulled from PlantVillage, building smarts over time. Rather than starting fresh, it fine-tunes existing models like ResNet or MobileNet for better speed and precision. Tests confirm it’s spot-on when identifying problems, delivering quick answers without heavy gear. Because it works offline and costs little, growers get help exactly when needed - boosting harvests while supporting smarter, greener farms.},
        keywords = {CNN, Plant Disease Detection, Deep Learning, Transfer Learning, Mobile Application, Smart Agriculture.},
        month = {November},
        }