High-level Computer Vision
Computer vision is A knowledge domain scientific field that compacts with however computers will gain high-level understanding from digital pictures or videos. From the angle of engineering, it finds to know and modify tasks that the human sensory system will do. Computer vision tasks contain strategies for effort, processing, analyzing and understanding digital pictures, and removal of high-dimensional
information from the particular world so as to form numerical or symbolic data, e.g. within the kinds of selections. Understanding during this context means that the transformation of visual pictures (the input of the retina) into descriptions of the globe that add up to thought procedures and may elicit applicable action. This image understanding is often seen because the disentangling of symbolic data from image
information by models created with the help of pure mathematics, physics, statistics, and learning theory. The subject field of pc vision is anxious with the speculation behind artificial systems that excerpt data from pictures. The image
information will take many forms, like video sequences, views from multiple cameras, multi-dimensional
information from a 3D scanner or medical scanning device. The technological correction of pc vision seeks to use its theories and models to the structure of pc vision systems. Sub-domains of
High Impact List of Articles
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Taking a Moment to Pay Respects to People with Type-2 Diabetes
Puziah Y, Hamidah H & Azian AL
Research Article: Diabetes Management
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Taking a Moment to Pay Respects to People with Type-2 Diabetes
Puziah Y, Hamidah H & Azian AL
Research Article: Diabetes Management
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Counterfeit diabetes products and the ethical question of access
May M Cheng & Christelle Gedeon
Commentary: Diabetes Management
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Counterfeit diabetes products and the ethical question of access
May M Cheng & Christelle Gedeon
Commentary: Diabetes Management
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Using salivary biomarkers to identify children at risk of Type 2 diabetes
J Max Goodson & Francine K Welty
Editorial: Diabetes Management
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Using salivary biomarkers to identify children at risk of Type 2 diabetes
J Max Goodson & Francine K Welty
Editorial: Diabetes Management
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The future of diabetes prevention: a focus on the implications of the Diabetes Prevention Program Outcomes Study
Tania Acosta, Rafael Gabriel,Jaakko Tuomilehto
: Diabetes Management
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The future of diabetes prevention: a focus on the implications of the Diabetes Prevention Program Outcomes Study
Tania Acosta, Rafael Gabriel,Jaakko Tuomilehto
: Diabetes Management
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The key to managing diabetes in children and adolescents
Lori Laffel
: Diabetes Management
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The key to managing diabetes in children and adolescents
Lori Laffel
: Diabetes Management
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Addressing diabetes racial and ethnic disparities: lessons learned from quality improvement collaboratives
Abigail E Wilkes, Kristine Bordenave, Lisa Vinci & Monica E Peek
Review Article: Diabetes Management
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Addressing diabetes racial and ethnic disparities: lessons learned from quality improvement collaboratives
Abigail E Wilkes, Kristine Bordenave, Lisa Vinci & Monica E Peek
Review Article: Diabetes Management
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