I want to create AI using my own data.
How can I assure the data security?
How much is the development cost?
This product is to create an AI for item classification captured in an image file, using your own data easily.
There ara a variety of commercial software products which include AI logic for images. When you try to utilize them, you often confront difficulties in detections on your own product images. The reason is, the system doesn't use your own image files for your products when it creates the AI logic.
If you want to create an AI which integrates with your own image files, you will develop a new system internally, or ask the other system development company.
Most of books on AI describe complex mathematics. Deep understanding of the contents is necessary to develop your own system with AI. Therefore, selecting internal development option is difficult from cost and time point of views for many companies.
On the other hand, asking the other company has the other issues. Your image files may include products which are not released. Or, anyone may be able to identify a specific person by those images. One more issue is, the total cost will be extremely high to develop your own sytem, compared to commercial products.
ezDeep IC is a product which solves those issues, and the benefits are as follows.
Image classification is to let AI detect what is captured in a specific image file.
This image explains recognition whether vegetable or fruit. This technology is often used in various business areas. NG product detection is one example.
This product has a lot of features which allow you to create your own AI for image classification easily.
The basic operation is just placing your image files, which you want to integrate with your AI logic, at pre-defined folder, and classifying those. Neither technical knowledge nor programinng is required.
You can create your own AI data by similar operations to commercial image processing software products.
Once you finalize classifications on all images, you will use Deep Learning feature to create your own AI logic with your own image information.
You can confirm the result of each trial on a dialog box during repeated calculations.
The calculation error during deep learning is shown immediately.
You can confirm the status on both learning and testing data as dedicated graphs. Stop your deep learning at an appropriate time, watching the trend of the error values.
Once you finalize deep learning, you can see classification result with an image file.
The system will display the image used for result confirmation, the detected classification, and the possibility.
If the result is not as expected, repeat data creation and deep learning.
ezDeep IC data keeps all internal parameters after Deep Learning. Development kit allows you to develop your own system which utilizes your own AI logic.
You can change the AI logic just by reloading ezDeep IC data. Therefore, you may not need to develop the system again, in the case of constructing AI for your new product release. Shorter product release time, and less system development cost, would be expected, because many tasks can be conducted internally.
A dedicated software can be used for your layer design in your deep learning network. You can specify each layer type, its parameters, or others without any programming.
When you start your own project, you may have many things you don't understand, such as what kind of architecture you should select for your network, and how you should utilize ezDeep features. We've been collected so much data, created many network architectures, and executed deep learning repeatedly, through our product development. Our technical knowledge on AI, acquired through our development process, will support your project execution steadily.
The bigger your AI network is, the faster the calculation speed must be. Therefore, this system adopted multi-thread technology for many of calculation processes. High performance CPUs have a lot of cores. You can also select a hardware with multiple CPUs. You can expect faster calculation speed with such high performance hardware by multi-thread parallel processes.
Many AI projects use GPU to improve calculation speed. Thus, this system supports calculations with GPU. This technology may also improve calculation speed.