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Image Recognition Technology Product List

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Robot and AI technology consultation desk

Robot and AI technology consultation desk

We accept inquiries from customers who want to use robots and AI.

We propose optimal solutions based on our extensive experience in robotics, AI, and sensing. Examples: 1. Automation of on-site tasks Unmanned operation of large plant auxiliary vehicles / Automation of floor cleaning / Pipe wall thinning detection system / Unmanned construction through remote operation 2. Automation of office desk work Routine administrative processing / Management of abnormal signs in plants 3. New business development using robots Unmanned operation in oxygen-deficient tasks / Non-destructive testing equipment for plants / Automation of existing conveyor systems using robots

  • Road construction
  • Railway Construction
  • Transport machinery
  • Image Recognition Technology

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Image recognition technology "Furinkazan Pose"

Image recognition technology "Furinkazan Pose"

Instantly recognize the skeletal structure of a person captured in the camera image.

"Furinkazan Pose" is an unprecedented high-speed skeletal estimation technology in the world. It can estimate with reasonable accuracy at a speed of 60 FPS, even on an embedded computer like the Jetson Nano. By leveraging low costs, it can be installed in large quantities, and by utilizing high-speed operation, it can analyze intense movements. 【Features】 ■ Moves at the edge and visualizes human posture in real-time ■ Various applications such as sports analysis and fall detection *For more details, please download the PDF or contact us.

  • Other Software
  • Image Recognition Technology

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Automation of routine office desk work

Automation of routine office desk work

Automating routine office desk work that requires human effort.

Automate processes in administrative workflows where human intervention is involved, such as manually transferring result data from one worksheet to another. If the administrative tasks are already standardized and based on past experience, let the electronic clerk handle them. First, we will consider automating the business as it currently stands to achieve rationalization and gain benefits more easily and quickly. Our self-developed intelligent technology for robot control can also be useful in administrative processing IT (information technology).

  • Sales promotion and sales support software
  • Image Recognition Technology

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Device control development using AI that can be operated without touch.

Device control development using AI that can be operated without touch.

Image recognition using deep learning, operating a robot with hand gestures.

Three-dimensional objects are identified by artificial intelligence through deep learning. Edge computing is also possible. When a hand is captured by a camera, the AI determines its shape, and the robot moves according to the instructions. Our algorithm can recognize hand shapes in about 20ms, allowing for real-time and smooth operation of the robot. You can easily control the robot just by holding your hand in front of the camera. Additionally, it can be applied to various machine controls, such as when hands are dirty and cannot touch a panel, when wearing gloves that do not respond to touch screens, or when one does not want to hold a controller. Edge computing is also possible with devices like Raspberry Pi.

  • Other measuring instruments
  • Image Recognition Technology

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[Case Study] Various Initiatives for Digital Home Appliances

[Case Study] Various Initiatives for Digital Home Appliances

Reducing processing load using transfer learning and learning models! A case of achieving automatic recipe suggestions.

The customer had the challenge of wanting to "implement image recognition technology that recognizes ingredients with a camera, and after correctly identifying the ingredients, propose recipes linked to the dishes." In implementing the image recognition technology, it was necessary to accurately recognize the materials with the camera, and to reduce processing load, transfer learning and a learning model (mobilenet) were used to ensure it could also operate on small PCs like Raspberry Pi. In recognizing work processes, the system was designed to recognize the work status at each stage with a camera, identify how far along the process is, and determine what the next step is, including follow-up to the next stage. Additionally, there are examples of product control through gestures. For more details, please refer to the related links below. [Case Overview (Partial)] ■ Client Industry: Electronics ■ Service Line: Technology / IoT *For more details, please refer to the PDF materials or feel free to contact us.

  • others
  • Image Recognition Technology

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