A flexible framework for automated STED super-resolution microscopy. [PDF]
Hörl D.
europepmc +1 more source
Geometry‐Aware Alignment and Comparison of Hierarchical Morse Complexes with Applications
Abstract Scalar fields derived from 3D X‐ray CT scans of samples undergoing ex situ processes, such as thermal aging, chemical etching, or mechanical stress, pose unique challenges for characterizing similarities and differences across acquisitions. Typically, a sample A (source) is imaged, removed, and subjected to experimental conditions that alter ...
Aniketh Venkat +3 more
wiley +1 more source
AI-enhanced routing and slicing strategy for QoS-aware mobile ad hoc networks. [PDF]
C V +5 more
europepmc +1 more source
Effect of stop line detection in queue length estimation at traffic signals from probe vehicles data
Gurcan Comert
semanticscholar +1 more source
Abstract Network visualization has traditionally relied on heuristic metrics, such as stress, under the assumption that optimizing them leads to aesthetic and informative layouts. However, no single metric consistently produces the most effective results.
X. Li, P. Zhang, X. Wang, H. Shen, Y. Hu
wiley +1 more source
Research on path planning algorithms for Crawler transport robots in complex tunnels. [PDF]
Yu T +9 more
europepmc +1 more source
Clusterix: A Hybrid Visualization Model for Hierarchically Clustered Networks
Abstract We introduce Clusterix, a novel hybrid visualization model for representing hierarchically clustered networks, which also supports directed and weighted edges. Clusterix offers an integrated view of both the network and its full cluster hierarchy by compactly visualizing the cluster inclusion tree enriched with links of the network.
Carla Binucci +6 more
wiley +1 more source
Cloud-Edge Resource Scheduling and Offloading Optimization Based on Deep Reinforcement Learning. [PDF]
Yin L, Xie Y, Zhao Z, Gao J.
europepmc +1 more source
Differentiable Randers‐Finsler Eikonal Solvers
Abstract Fast and differentiable solvers for anisotropic and asymmetric distance fields are a key primitive in geometry processing, enabling gradient‐based optimization over metrics, drift fields, and downstream objectives that depend on geodesic distances and geodesics.
Barak Gahtan +2 more
wiley +1 more source
Higher-Order Markov Model-Based Analysis of Reinforcement Learning in 6G Mobile Retrial Queueing Systems. [PDF]
Talbi D, Gal Z.
europepmc +1 more source

