Dec 15, 2021 · We review methods, empirical findings, theories, and prescriptions across the fields of visual perception, graph comprehension, information visualization, data-based reasoning, uncertainty representation, and health risk communication.

Dec 25, 2019 · Graph nodes in visual connectivity analysis can have any number of connections, as opposed to the spatial connectivity’s maximum of eight. The product of both analyses is a coloured map that describes areas with high or low connectivity and visibility (see Figure 2 for a comparative example).

Jul 19, 2015 · In this paper, we argue that by positioning visual representations as epistemic objects of scientific practices, science education can bring a renewed focus on how visualization contributes to knowledge formation in science from the learners’ perspective.

establish that weighted graph comparisons can benefit a group of higher-level tasks in visual brain connectivity analysis. We explored alternative visual encodings that facilitate the com-parison of edge weights across two graphs in a superimposed view, both in node-link diagrams and adjacency matrices.

Sep 1, 2024 · Graph representation learning (GRL) is an efficient data mining and machine learning method for network analysis tasks like network reconstruction, node classification, and link prediction. Identifying an appropriate GRL model for specific tasks is necessary before network analysis.

Presented here are ten principles that serve as guidance for authors who seek to improve their visual message. Some principles are less technical, such as determining the message before starting the visual, while other principles are more technical, such as how different color combinations imply different information.

4 days ago · D.-K. Nguyen, T. Okatani, Improved fusion of visual and language representations by dense symmetric co-attention for visual question answering, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 6087–6096.

Jan 21, 2025 · By integrating attention-guided visual representations with graph-enhanced features, our method offers a more comprehensive understanding of spatial and contextual information, resulting in enhanced performance in reasoning-based VQA tasks.

Through the proposed internal visual connectivity analysis framework, we aim to better assess an occupant’s visual experience inside a building through quantitative means and further

A scene graph is a structured representation that captures not only the objects present in an image but also their attributes and the relationships that exist among them.