According to new research by LogicPlum, disease in rice plants can result in no grain harvest; therefore, detecting disease early and providing expert remedies in a low-cost solution is highly desirable
The researchers studied a pragmatic approach for rice growers to leverage artificial intelligence solutions that reduce cost, increase speed, improve ease of use, and increase model performance over other solutions.
“Our recent publication demonstrates the unique capability of translating LogicPlum AI and machine learning into solutions that can support crucial global industries like agriculture,” noted Damian Mingle, LogicPlum founder.
“This is an example of just one of the many problems we can help solve. We improved on the benchmark for rice plant disease classification by a significant margin and at the same time, we scaled our deep-learning model down to under 50 MB, allowing it to be used anywhere, without an internet connection. This is expert knowledge, accessible and available to help workers address problems immediately – farmers are no different. At its core, LogicPlum asks for organisational challenges so we can showcase how technology works in context, turning tech that has traditionally been considered impractical into the practical. One of the core tenants of what we believe is that innovation is not providing fancy algorithms, but rather value to the customer,” he added.
LogicPlum: AI solutions for real-world problems
“With our recently published work, we aimed to keep things simple,” said Amit Kumar, machine learning researcher at LogicPlum.
“Farmers and growers weren’t just having a hard time detecting disease correctly, but correctly knowing what to do next. That’s something we can help solve, both academically and with practical applications. LogicPlum refuses to be defined by someone else’s vision of what’s possible. And, we have now taken these deep learning approaches to the farmer’s field, putting them directly in the hands of farmers and administrators via smartphones – providing them real-time insights for cultural, preventive, and chemical methods that they can use.”
