The learning model is built from scratch on AWS! We provide our technology and ideas.
We have built an application system using Deep Learning that operates on a Raspberry Pi3 as a proposal for AI solutions for edge devices. At Embedded Technology 2016 / Comprehensive Embedded Technology Exhibition, we conducted a technical demo of a blood type determination app using PiCamera. Anticipating various future needs and versatility, we created it from scratch on AWS using a Deep Learning framework without relying on existing pre-trained models. We provide technologies and ideas that can flexibly adapt to and control the embedded devices envisioned by our customers. *For more details, please refer to the PDF materials or feel free to contact us.
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basic information
【System Contents】 ■dlib ・Face recognition library ・Used for extraction from material data (face photos) ■chainer ・Deep Learning framework ・Chose chainer for its ease of use and simplicity ■AWS ・Training model is trained on AWS GPU instances ・Using p2.xlarge on Amazon EC2 P2 instance ■PyQt4 ・Used for creating GUI ■PiCamera ・Camera library for Pi ・Used for taking photos with the main unit ■Anaconda3-4.0/Miniconda3.4 ・Pytorch distribution ・For Raspberry Pi 3, configured minimally with Miniconda ■RaspberryPi3/Raspbian ・Keeps the training model locally and operates entirely locally *For more details, please refer to the PDF document or feel free to contact us.
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For more details, please refer to the PDF document or feel free to contact us.
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At Bee, we handle not only embedded software development but also the development of associated applications and cloud/AI solutions in a comprehensive manner, following innovative technologies that are not confined to traditional embedded software frameworks. We are certified under the information security management system standard "ISO/IEC 27001:2013" in customer requirements as well as in the design, development, and maintenance of our proprietary software. Furthermore, while "DX transformation" is being emphasized in recent times, we have achieved paperless and cloud-based operations since our founding in 2006, considering improvements in both information security and the internal environment as standard practice.
