Our approach consists of (a) analyzing and characterizing heat diffusion traces in directed graphs, and (b) extending the thermodynamic depth framework to capture the second-order variability of the diffusion traces to measure the complexity of directed networks. We provide experiments on real-world ...
and is defined in terms of computational complexity. Depth quantifies the length of the shortest parallel computation required to construct a typical system state or history starting from simple initial conditions. The properties of depth are discussed and it is compared to other complexity ...
2) A fast depth filling strategy (DSR_F) is proposed, which inherits the advantages of low complexity and high accuracy from local and global methods respectively, and therefore achieves far better performance than traditional local or global methods. 3) A cascaded edge inference and depth restora...
In\({\mathbb {R}}^1\), both Tukey and Tverberg depth give a very natural depth measure: it counts the number of points ofSto the left and to the right ofqand then returns the minimum of the two numbers. We call this measure thestandard depthin\({\mathbb {R}}^1\). In particula...
“Mono." refers to “Monocular", and “multi-tasks" means that in addition to pose and depth estimation, there are other tasks that are jointly trained in the framework, such as semantic segmentation, motion segmentation, optical flow, camera intrinsic, objects motion, surface normal, etc. ...
Current approaches to classifying agentic demands of PHIs are inadequate for capturing their nuance and diversity. A framework to achieve this has potential to improve evidence synthesis by providing a consistent and comprehensive approach to classifying agentic demand. Such a framework may also inform ...
A fast strategy by replacing the global cross correlation with a nonlocal affinity is proposed to reduce the implementation complexity without sacrificing the estimation performance. Combining with a channel attention module, we apply the dual-attention module on top of the backbone in contextual ...
This study investigates the alignment of AI-generated tasks with the SOLO taxonomy, a cognitive framework used in educational assessment to classify learning outcomes based on their complexity. As AI technologies increasingly contribute to educational assessments, ensuring that generated content aligns with...
Downgrading .Net Framework 4.0 to 3.5 Download Windows Server Essentials to USB DsBindWithSpnEx() failed with error -2146893022 : DCDIAG DSRM password does not meet complexity requirements duplicate (potentially the shorter NETBIOS) name exists on the network? Win2008R2 Duplicate Groups in AD Dupli...
Complexity allocation is then utilized to ensure that each CTU is provided an optimum complexity. A probability-based CTU depth range adjustment process is utilized to select an appropriate depth range for each CTU. A feedback-based complexity control framework is implemented, which consists of ...