image understanding - définition. Qu'est-ce que image understanding
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Qu'est-ce (qui) est image understanding - définition

COMPUTERIZED INFORMATION EXTRACTION FROM IMAGES
Computer Vision; Image recognition; Computer vision systems; Image Recognition Techniques; Computational vision; Image understanding; Image Understanding; Image Recognition; Image classification; Computational Vision; Texture recognition; History of computer vision; Visual recognition software; Applications of computer vision; Computer vision intelligence; Computer visual intelligence; Image classifier; Shape recognition; Visual recognition; Image identification; Classification of images; Image-based artificial intelligence; Military applications of computer vision
  • [[DARPA]]'s Visual Media Reasoning concept video
  • Rubber artificial skin layer with the flexible structure for the shape estimation of micro-undulation surfaces
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  • Above is a silicon mold with a camera inside containing many different point markers. When this sensor is pressed against the surface the silicon deforms and the position of the point markers shifts. A computer can then take this data and determine how exactly the mold is pressed against the surface. This can be used to calibrate robotic hands in order to make sure they can grasp objects effectively.
  • Learning 3D shapes has been a challenging task in computer vision. Recent advances in [[deep learning]] have enabled researchers to build models that are able to generate and reconstruct 3D shapes from single or multi-view [[depth map]]s or silhouettes seamlessly and efficiently.<ref name="3DVAE" />

Medical Image Understanding and Analysis conference         
Medical Image Understanding and Analysis; MIUA
Medical Image Understanding and Analysis (MIUA) is a UK-based meeting for the communication of research related to image analysis and its application to medical imaging and biomedicine. The meetings provide an opportunity to present and discuss research in medical image understanding and analysis; a rapidly growing subject with ever increasing real-world applicability.
Computer vision         
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
computer vision         
A branch of artificial intelligence and image processing concerned with computer processing of images from the real world. Computer vision typically requires a combination of low level image processing to enhance the image quality (e.g. remove noise, increase contrast) and higher level pattern recognition and image understanding to recognise features present in the image. Usenet newsgroup: news:comp.ai.vision. (1994-11-30)

Wikipédia

Computer vision

Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.

The scientific discipline of computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, multi-dimensional data from a 3D scanner, or medical scanning devices. The technological discipline of computer vision seeks to apply its theories and models to the construction of computer vision systems.

Sub-domains of computer vision include scene reconstruction, object detection, event detection, video tracking, object recognition, 3D pose estimation, learning, indexing, motion estimation, visual servoing, 3D scene modeling, and image restoration.

Adopting computer vision technology might be painstaking for organizations as there is no single point solution for it. There are very few companies that provide a unified and distributed platform or an Operating System where computer vision applications can be easily deployed and managed.