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Artificial intelligence based on machine vision
Artificial intelligence based on machine vision
Chu Dianhui
领军人物Chu Dianhui
Researcher, Beijing Normal University Senior Engineer Beijing Normal University (Zhuhai) Complex Systems International Science Center special researcher, senior engineer, Shandong automation society director. Long-term engaged in visual-based artificial intelligence and automatic control research.

Product orientation

1. high performance eye movement instrument (brain function detector)

2.MODBUS protocol I/O board

3. Brain Function Detector Database System

4. Brain Cognitive Function Experiment Interface and Test Tool Platform

5. Product Grade Detection and Control System Based on Machine Vision

6. Machining Path Location for Machine Vision Planning

7. Motion Control System

 

Application scenarios

 

 

 

1. Perceived Security

(1) Classical measurement techniques

(Measuring techniques around seven basic physical quantities and their derivatives in the international system of units)

Length: m (m)

Time: seconds (S)

Mass: kg (kg)

Current: Ampere (A)

Temperature: Kelvin (K)

Physical quantities: mole (mol)

Illumination: Candela (cd)

(2) New Generation of Intelligent Perception Technology

Brain-inspired Intelligent Perception

Visual auditory tactile taste

Intelligent Perception Based on Big Data

Feature extraction for pattern recognition

Intelligent perception of machine learning, deep learning and reinforcement learning

New Generation Intelligent Sensor Technology

Embedded Intelligent Terminal

Edge calculation

 

2. Intelligent Decision

(1) Classic decision-making

Based on deterministic logic

Limited by the designer's cognitive level

Closed system based

(2) Intelligent decision-making technology

Based on interpretable models

Sample size

Weak supervised learning

Intelligent Cognition of Multi-modal Intelligent Computing

Intelligent Autonomous Learning and Evolution

 

3. Intelligent Cognition

(1) Classical Cognitive Technology and Weak Artificial Intelligence

Knowledge Base

Limited by the designer's cognitive level

Closed system based

(2) Intelligent Cognitive Technology

Based on interpretable models

Sample size

Weak supervised learning

Intelligent Cognition of Multi-modal Intelligent Computing

Intelligent Autonomous Learning and Evolution

 

4. Intelligent Execution

(1) Classic execution model

Based on the determination process, results

Process determination based on manual design

Traditional Open Control Model

(2) Intelligent execution

Adaptive Flexible Manufacturing Execution

Intelligent robot

Agile Manufacturing

On-line Intelligent Technology

Digital twinning of execution process