A Bio-Inspired Visual Neural Model for Robustly and Steadily Detecting Motion Directions of Translating Objects Against Variable Contrast in the Figure-Ground and Noise Interference

A Bio-Inspired Visual Neural Model for Robustly and Steadily Detecting Motion Directions of Translating Objects Against Variable Contrast in the Figure-Ground and Noise Interference

(1) Background: At present, the bio-inspired visual neural models have made significant achievements in detecting the motion direction of the translating object. Variable contrast in the figure-ground and environmental noise interference, however, have a strong influence on the existing model. The r...

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Bibliographic Details
Main Authors: Sheng Zhang, Ke Li, Zhonghua Luo, Mengxi Xu, Shengnan Zheng
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Biomimetics
Subjects:
Drosophila
LPTC neurons
motion directions
translating objects
variable contrast in figure-ground
environmental noise interference
Online Access:https://www.mdpi.com/2313-7673/10/1/51
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