[HTML][HTML] A Looming Spatial Localization Neural Network Inspired by MLG1 Neurons in the Crab Neohelice

H Luan, Q Fu, Y Zhang, M Hua, S Chen… - Frontiers in …, 2022 - frontiersin.org
Similar to most visual animals, the crab Neohelice granulata relies predominantly on visual
information to escape from predators, to track prey and for selecting mates. It, therefore …

Characterization and modelling of looming-sensitive neurons in the crab Neohelice

J Carbone, A Yabo, D Oliva - Journal of comparative physiology A, 2018 - Springer
Looming-sensitive neurons (LSNs) are motion-sensitive neurons tuned for detecting
imminent collision. Their main characteristic is the selectivity to looming (a 2D representation …

Computation of object approach by a system of visual motion-sensitive neurons in the crab Neohelice

D Oliva, D Tomsic - Journal of neurophysiology, 2014 - journals.physiology.org
Similar to most visual animals, crabs perform proper avoidance responses to objects directly
approaching them. The monostratified lobula giant neurons of type 1 (MLG1) of crabs …

Object approach computation by a giant neuron and its relationship with the speed of escape in the crab Neohelice

D Oliva, D Tomsic - Journal of Experimental Biology, 2016 - journals.biologists.com
Upon detection of an approaching object, the crab Neohelice granulata continuously
regulates the direction and speed of escape according to ongoing visual information. These …

Shaping the collision selectivity in a looming sensitive neuron model with parallel on and off pathways and spike frequency adaptation

Q Fu, C Hu, J Peng, S Yue - Neural Networks, 2018 - Elsevier
Shaping the collision selectivity in vision-based artificial collision-detecting systems is still an
open challenge. This paper presents a novel neuron model of a locust looming detector, ie …

A network of visual motion-sensitive neurons for computing object position in an arthropod

V Medan, MB De Astrada, F Scarano… - Journal of …, 2015 - Soc Neuroscience
Highly active insects and crabs depend on visual motion information for detecting and
tracking mates, prey, or predators, for which they require directional control systems …

Enhancing LGMD's looming selectivity for UAV with spatial–temporal distributed presynaptic connections

J Zhao, H Wang, N Bellotto, C Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Collision detection is one of the most challenging tasks for unmanned aerial vehicles
(UAVs). This is especially true for small or micro-UAVs due to their limited computational …

Shaping the ultra-selectivity of a looming detection neural network from non-linear correlation of radial motion

M Hua, Q Fu, J Peng, S Yue… - 2022 International Joint …, 2022 - ieeexplore.ieee.org
In this paper, a numerical neural network inspired by the lobula plate/lobula columnar type II
(LPLC2), the ultra-selective looming sensitive neurons identified within visual system of …

Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons

B Zhou, Z Li, S Kim, J Lafferty, DA Clark - Elife, 2022 - elifesciences.org
Animals have evolved sophisticated visual circuits to solve a vital inference problem:
detecting whether or not a visual signal corresponds to an object on a collision course. Such …

A neural model of the locust visual system for detection of object approaches with real-world scenes

MS Keil, E Roca-Moreno… - arXiv preprint arXiv …, 2018 - arxiv.org
In the central nervous systems of animals like pigeons and locusts, neurons were identified
which signal objects approaching the animal on a direct collision course. Unraveling the …