Results 181 to 190 of about 14,217 (252)
Reflections on Traceability for Visualization Research
Abstract Decades of advocacy for reproducibility and replication have advanced open, transparent practices in the sciences. However, traditional notions of reproducibility fit poorly with design‐oriented visualization research, where insights emerge through subjective, situated, and iterative work.
J. Rogers +4 more
wiley +1 more source
ReSurfEMG: A Python Package for Comprehensive Analysis of Respiratory Surface EMG. [PDF]
Warnaar RSP +5 more
europepmc +1 more source
SlideSAVR: Enabling Live Analysis during Data Presentations via Multimodal Sketching and Voice Input
Abstract Interpersonal communication in data science can yield sought‐after insights, but presentation environments are often not conducive for live analysis, forcing the process to move offline. Through a formative survey with 16 participants, we identified both technical (e.g., complexity of tools) and psychological (e.g., pressure of programming ...
C. Han +5 more
wiley +1 more source
Ten simple rules for making biomedical data resources accessible. [PDF]
Smits TC, Weru L, Gehlenborg N, L'Yi S.
europepmc +1 more source
BloomTree: Dynamic Coloring Techniques for Exploring Deep and Wide Tree Structures
Abstract This study introduces BloomTree, an interactive Sunburst system for visualizing massive hierarchical datasets, such as the Tree of Life. Traditional static color schemes fail to maintain perceptual distinguishability when applied to millions of nodes, and managing the full tree in memory is computationally costly.
A. Tanaka, K. Wakita
wiley +1 more source
A Pragmatic Framework for Federated Learning Risk and Governance in Academic Medical Centers. [PDF]
Bottomly D +6 more
europepmc +1 more source
Visualizing Image Segmentation Network Behavior Through the Lens of Scale Space Analysis
Abstract Deep neural networks are widely used for image segmentation, also in sensitive applications such as medical imaging or autonomous driving. However, few explainable AI methods are available that help developers understand such networks beyond classification.
A. C. Mikliss, T. Schultz
wiley +1 more source
Data welfare is animal welfare: Building a WellFAIR research ecosystem. [PDF]
Petit-Demoulière B, Huzard D.
europepmc +1 more source

