Immersive Data Comprehension: Visualizing Uncertainty in Measurable Models
نویسندگان
چکیده
منابع مشابه
Immersive Data Comprehension: Visualizing Uncertainty in Measurable Models
Recent advances in 3D scanning technologies have opened new possibilities in a broad range of applications including cultural heritage, medicine, civil engineering, and urban planning. Virtual Reality systems can provide new tools to professionals that want to understand acquired 3D models. In this review paper, we analyze the concept of data comprehension with an emphasis on visualization and ...
متن کاملVisualizing Uncertainty in Predictive Models
In many scientific fields, models are used to characterize relationships and processes, as well as to predict outcomes from initial conditions and inputs. These models can support the decision-making process by allowing investigators to consider the likely effects of possible interventions and identify efficient ways to achieve desired outcomes. Machine learning research on constructing complex...
متن کاملVisualizing Data with Bounded Uncertainty
Visualization is a powerful way to facilitate data analysis, but it is crucial that visualization systems explicitly convey the presence, nature, and degree of uncertainty to users. Otherwise, there is a danger that data will be falsely interpreted, potentially leading to inaccurate conclusions. A common method for denoting uncertainty is to use error bars or similar techniques designed to conv...
متن کاملVisualizing uncertainty in spatio-temporal data
Analyzing the relationship between location and time in a spatio-temporal data is not trivial. It is even more challenging if the data contains uncertainty. In this paper, we present a new method that visualizes spatio-temporal data with uncertainty. This method is an extension of our 2D visualization technique called Storygraph, and it handles two types of data uncertainty: (1) the spatial and...
متن کاملVisualizing uncertainty in biological expression data
Expression analysis of ∼omics data using microarrays has become a standard procedure in the life sciences. However, microarrays are subject to technical limitations and errors, which render the data gathered likely to be uncertain. While a number of approaches exist to target this uncertainty statistically, it is hardly ever even shown when the data is visualized using for example clustered hea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Robotics and AI
سال: 2015
ISSN: 2296-9144
DOI: 10.3389/frobt.2015.00022