Overview

This kit makes it easy to evaluate image recognition using the "UncannyDL" deep learning library for embedded devices developed by Uncanny Vision (Head Office: India).
This helps shorten development times and reduce costs for deep learning systems.


* Click to enlarge

Features

・ Unique technology delivers fast and accurate CNN learning
・ Fully edge-based image recognition (no cloud or network connection required)
・ Execution speed 2 to 4 times faster than Caffe with only 1/3 of the memory space
・ CNN learning time greatly shortened from several months to one week
・ Optimized for embedded applications 



Use cases

・ Image recognition in edge devices
・ Intelligent IoT
・ Antitheft or surveillance devices
・ Machine vision
・ Human behavior recognition
・ Abnormality recognition
・ AR, computer games

Specifications and price

 Kit KitA KitB
KitC
 Number of recognition targets Up to 5 types Up to 10 types 10 types or more
Minimum number of images per recognition target 300
300 300
Number of times CNN learning performed Up to 1 time Up to 2 times (*)
Number of times images uploaded
Up to 1 time
Up to 2 times
(*)
Deliverable
Image recognition app
(supports Android or Linux) 
Image recognition app
(supports Android or Linux) 
Image recognition app (*)
(supports Android, Linux, or other operating system)
Price \ 500,000 \ 800,000 (*)
* Determined based on user request.


Main flow for use

・ Purchase Kit (A/B/C) according to user request
・ Install dedicated app for Android smartphones
・ Collect or shoot images for deep learning
・ After collecting or shooting sufficient images for each recognition target, upload the images to the specified server
 - At least 300 images required for each recognition target, no upper limit
 - Can be uploaded from a smartphone app or PC application
・ After about 1 week, an app that can recognize each target is provided as a deliverable from Uncanny Vision 

Example of actually using an image recognition app

・ The app provided by Uncanny Vision with machine learning completed is installed.
・ When the recognition target image is shot, the deep learning recognition operation is started.
・ The recognition result and probability are displayed on the screen.





Precautions

・ The recognition target is limited to objects and scenes.
・ The CNN to use for learning is selected by Uncanny Vision.
・ Because the learning process of deep learning starts as soon as the learning images are uploaded,
 please collect or shoot sufficient images before uploading them. 
・ The app cannot be used after the predetermined number of times of performing learning has been reached. 
・ The expected image recognition rate is about 80%. However, because this depends on the quality of the learning images and the number of images provided,
 this is not a guaranteed value. 

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