The more pictures you take, the more accurate the results.
We use the cutting edge deep learning algorithms to classify the plant.
All your results are stored in the app, so you can return to them whenever you like.
The smartphone app has been initially developed for the iPhone4, 4s, 5, and 5s running iOS7. We hope to release on the App Store as soon as possible.
The team uses Node.js and MongoDB to administer the server-side functionality. Our server architecture has been built with scale in mind. Even as our app becomes more popular, users can still expect quick response times.
The neural network is based on Alex Krizhevsky's cuda-convnet library. The heart of the implementation uses NVIDIA's CUDA platform; a proprietary language that provides extensions to C++ allowing developers access to CUDA-enabled GPUs.
Gerard is the team leader and scrum master.
He works on the Data Infrastructure, and general NoSQL wizardry.
Ashley is the team's front-end developer.
He focuses on the app's development, working primarily in Objective-C.