… We found that study characteristics such as study class and sample size influenced the effect
sizes of the two models on students’ mathematical abilities. However, study characteristics …

… geometric deep learning and related methods. First, we introduce the relevant knowledge
and history of geometric deep learning … review different graph network models for graphs and …

… for the evaluation of the optical flow model. The evaluation process is the same for all optical
flow evaluations in this paper including the ablation study. Note that 3 cascaded networks …

… Site-specific propagation modeling is one of the typical geometrical modeling … environment,
leading to reflection, scattering, diffraction, and penetration. Therefore, geometrical modeling …

… and are stable across repeated visits to the same environment 13 . This suggests that
these cells code for geometric environmental features, irrespective of low-level sensory …

… In this work, we have proposed an SNN model implementing associative learning
through an STDP protocol and temporal coding of sensory stimuli. To achieve successful …

Safety critical systems in Advanced Driver Assistance Systems (ADAS) depend on multiple
sensors to perceive the environment in which they operate. Radar sensors provide many …

… Visual perception of 3D scene geometry … geometry (depth and flow) of static and moving
objects in a 3D scene. Supervised deep learning models have been proposed for geometry pre…

… By developing models that contain several important variables relating to driver, roadway
conditions and geometry, vehicle types and crash characteristics, this study provides new …

… By estimating certain features of the built environment, we can predict positive healing …
human health as a result of the environmental geometry. The biophilic healing index is also very …