Quantitative Performance Optimisation for Corner and Edge Based Robotic Vision Systems: A Monte-Carlo Simulation

Tian, Jingduo; Thacker, Neil A.; Stancu, Alexandru

doi:10.1007/978-3-319-50832-0_53

Cited by 1 publication

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pattern recognition focuses on the classification of optical map, text, fingerprint, chromosome, and so on. Computer vision is to describe the scene of objects according to the situation of the image and to broaden and assist the visual function in a certain situation [17][18][19]. We can easily and consciously perceive the world around us through our eyes.…”

Section: Computer Vision Techniquesmentioning

confidence: 99%

A Framework for Green Interior Design and Simulation Using Immersive VR Technology

Yang

Xiao

Deng

2022

Mobile Information Systems

View full text Add to dashboard Cite

The green decoration indoor environment design method has become the main trend in recent years with the rising awareness of environmental protection. The green design strategy emphasizes the reduction of production materials, packaging materials, recycling of waste products, and material recycling. Generally, green interior design is a kind of cognition of friendly treatment to the environment. Considering the future use and development of space to adopt flexible strategies, the design process should incorporate the possibility of future changes. The flexible strategies can reduce the future part of the change and can redecorate waste. In the process of creativity and design, the design objectives should be clearly defined, and the frequency of modification should be reduced. This research introduces a framework for green interior design and simulation using immersive VR technology. The concept of regeneration is used to achieve maximum utilization and minimum damage. It improves the efficiency of using resources; on the other hand, it reduces the impact of interior design on human health and environment.

show abstract

Section: Computer Vision Techniquesmentioning

confidence: 99%