Want to say machine vision differently? Here are other words for machine vision and its similar synonyms and opposite words to say in unique way.
Meaning of machine vision
The primary meaning of "machine vision" refers to the ability of a machine to interpret and understand visual information from the world, using cameras, sensors, and artificial intelligence.
Etymology of machine vision
The term "machine vision" originated in the 1950s and 1960s, when computers were first being used to process and analyze visual information.
The field of machine vision has its roots in computer science, electrical engineering, and optics, and has evolved over time to incorporate advances in artificial intelligence, machine learning, and robotics.
Synonyms
computer vision
image processing
optical character recognition
object detection
facial recognition
image analysis
pattern recognition
artificial intelligence
deep learning
robotics
automation
surveillance
monitoring
inspection
quality control
defect detection
anomaly detection
image understanding
scene understanding
image recognition
machine learning
neural networks
convolutional neural networks
recurrent neural networks
transfer learning
object tracking
motion detection
image segmentation
feature extraction
image classification.
Definitions
- The use of computers to interpret and understand visual information from the world, using cameras, sensors, and artificial intelligence.
- A field of study that deals with the theory and application of computers to interpret and understand visual information.
- The ability of a machine to perform tasks that typically require human vision, such as object recognition, inspection, and tracking.
Usage Examples
- The factory uses machine vision to inspect products on the assembly line and detect any defects.
- The security system uses machine vision to detect and track intruders.
- The self-driving car uses machine vision to navigate and avoid obstacles.
Antonyms
human vision
natural vision
biological vision
manual inspection
human inspection
visual inspection
subjective evaluation
qualitative analysis
non-automated systems
traditional methods
outdated techniques
inefficient processes
inaccurate detection
false negatives
missed detections
incorrect classifications.