Machine Vision

Machine vision utilizes computer simulation of visual functions, capturing surrounding images through cameras or sensors, and then processing and analyzing these images using a computer. In this way, machines can "see" things and recognize their characteristics such as color and shape like humans.

The unit is designed for unsupervised public use: controls are recessed or shielded, moving parts are enclosed, and the interface is operable by a child of about six with no instruction. Where a screen is used, the language can be switched without changing the hardware, and the content can be replaced on site.

Machine imitates human senses: Machines are constantly imitating human senses, human learning abilities, etc., to achieve more advanced intelligence. At present, machines have achieved many human sensory abilities, such as vision vs machine vision, hearing vs speech recognition and synthesis, touch vs pressure sensors, smell vs machine nose, taste vs machine tongue, etc. By utilizing the powerful hardware computing capabilities, data cloud computing architecture, and intelligent algorithms, machines can break down the boundaries of the computing field and geography, and engage in deep autonomous learning, such as simulating real conversations with humans.