The Deep Learning technology LeapMind has cultivated " in a compact , simple to " device for providing
External all IoT devices and robot as an ultra- compact Deep Learning computer , consumer electronics , and provides a new value , such as the drone
How to use is simple , connected to the LeapMind to provide " Juiz Platform " ( 2016 year release schedule ) , it will be Deep Learning technology can be used only download the prepared recipe to device
Only the image data of the face , mirror -type device that can stress check in on time
Special camera is not required , we will analyzed by the algorithm .
Will the device to proceed to the usual day-to-day space only a little future .
For example, if you detect the stress is high when you're brushing your teeth in the bathroom the morning , such as the healing of travel information
How to use , such as it'll display it can be assumed to create a new Internet experience on the mirror device
This service analyzes the photos that have been posted on the SNS the consumer is represented by Instagram in DeepLearning technology
It will be marketing support services to perform a trend analysis .
Any potential information is on one of the photos we have reflected a lot .
However , although there was a limit only text mining is to get these potential data
It will be able to also collect potential data that could not be visualized until now by making use of the service .
Image identification and automatic tagging system , LeapMind is applying its own deep -learning technology , we are building .
By this time the newly constructed system , the food actual situation at the time of eating frozen food in an effort to provide to food-related companies
By the application of our own deep learning ( deep learning ) technology , the machine is to determine the contents of a photo sent from the consumer
Automatically it is possible to perform tagging .
This will be whether the consumer is what kind of diet to be able to visualize , Ya product development by food-related companies
It can be applied to the analysis of diet trends