Image recognition technology development - List of Manufacturers, Suppliers, Companies and Products

Image recognition technology development Product List

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Wide-ranging solutions: Fully customized image recognition and machine learning technology.

Wide-ranging solutions: Fully customized image recognition and machine learning technology.

Runner-up in an international competition for image recognition. Academic-level experts provide fully customized advanced solutions to clients' challenges.

CyberCore is a professional group of academic-level image processing researchers who come together to solve various challenges faced by clients using unique image processing and video processing algorithms, AI, and embedded technologies. In May 2018, we achieved the runner-up position in an international AI competition in the United States, and we are committed to providing world-class development capabilities. We offer customized solutions with advanced technical skills for challenges that are difficult to address visually. As of April 2018, we have a compact yet highly skilled development team of over 20 members domestically and over 10 members overseas (in Vietnam), which allows us to provide solutions that balance performance, cost, and speed to various clients. Examples of our solution achievements include: - Autonomous driving sensing-related technologies - Night vision and security cameras - Road and vehicle number recognition - Facial recognition systems - Drone 3D measurement systems - Automated advertising generation systems - Defective product inspection devices (AOI) - Fluid detection systems - Coin recognition systems

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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.

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