Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Tim Verbelen"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Cognitive problem-solving benefits from cognitive maps aiding navigation and planning. Physical space navigation involves hippocampal (HC) allocentric codes, while abstract task space engages medial prefrontal cortex (mPFC) task-specific cod
Externí odkaz:
https://doaj.org/article/d1a41f05384e49fb9056cfefb1946aba
Publikováno v:
IEEE Access, Vol 11, Pp 66934-66948 (2023)
Synthetic aperture radar (SAR) techniques are commonly used in spaceborne and airborne side-looking radar imaging applications, where the relatively high platform speeds enable the formation of very long synthetic apertures, which provide images with
Externí odkaz:
https://doaj.org/article/1db5e8e7401b40d3ba417f204bfef978
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 4, p 045012 (2024)
Tensor networks (TNs) have seen an increase in applications in recent years. While they were originally developed to model many-body quantum systems, their usage has expanded into the field of machine learning. This work adds to the growing range of
Externí odkaz:
https://doaj.org/article/e218d5bc7ace40578a852451fdf95f8c
Publikováno v:
Entropy, Vol 26, Iss 1, p 83 (2024)
Robust evidence suggests that humans explore their environment using a combination of topological landmarks and coarse-grained path integration. This approach relies on identifiable environmental features (topological landmarks) in tandem with estima
Externí odkaz:
https://doaj.org/article/1387541269ff43eeb99c1c78388ee50e
Publikováno v:
Frontiers in Systems Neuroscience, Vol 16 (2022)
Simultaneous localization and mapping (SLAM) represents a fundamental problem for autonomous embodied systems, for which the hippocampal/entorhinal system (H/E-S) has been optimized over the course of evolution. We have developed a biologically-inspi
Externí odkaz:
https://doaj.org/article/56acc0adf1d64c4a87650cf9689988f7
Autor:
Ali Safa, Tim Verbelen, Lars Keuninckx, Ilja Ocket, Mathias Hartmann, Andre Bourdoux, Francky Catthoor, Georges G. E. Gielen
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 9162-9175 (2021)
As radar sensors are being miniaturized, there is a growing interest for using them in indoor sensing applications such as indoor drone obstacle avoidance. In those novel scenarios, radars must perform well in dense scenes with a large number of neig
Externí odkaz:
https://doaj.org/article/0a4200911ca246d7bceecafc1634db24
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2022)
Scene understanding and decomposition is a crucial challenge for intelligent systems, whether it is for object manipulation, navigation, or any other task. Although current machine and deep learning approaches for object detection and classification
Externí odkaz:
https://doaj.org/article/36b558238eba41ee8fad01360caf97fa
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2022)
Although still not fully understood, sleep is known to play an important role in learning and in pruning synaptic connections. From the active inference perspective, this can be cast as learning parameters of a generative model and Bayesian model red
Externí odkaz:
https://doaj.org/article/0d96a3c0f5af45b5bbefdebd983bafd3
Publikováno v:
Sensors, Vol 22, Iss 19, p 7382 (2022)
The robotics field has been deeply influenced by the advent of deep learning. In recent years, this trend has been characterized by the adoption of large, pretrained models for robotic use cases, which are not compatible with the computational hardwa
Externí odkaz:
https://doaj.org/article/70b46f99982a42d6befbf3f7cc79fc49
Publikováno v:
Frontiers in Neurorobotics, Vol 15 (2021)
Occlusions, restricted field of view and limited resolution all constrain a robot's ability to sense its environment from a single observation. In these cases, the robot first needs to actively query multiple observations and accumulate information b
Externí odkaz:
https://doaj.org/article/5f800eb7302e4f14b206d1988b39c01c