AIMC Topic: Vision, Binocular

Clear Filters Showing 1 to 10 of 13 articles

StrabNet-CQ: an integrated deep learning framework for automated strabismus classification and quantification using ocular landmark detection.

BMC ophthalmology
BACKGROUND: Strabismus is a common ocular misalignment that can impair binocular vision if untreated. Conventional diagnosis and treatment rely on clinical prism diopter (PD) readings, which quantify deviation along with base direction. However, thes...

Decoding binocular color differences via EEG signals: linking ERP dynamics to chromatic disparity in CIELAB space.

Experimental brain research
This study explores how differences in colors presented separately to each eye (binocular color differences) can be identified through EEG signals, a method of recording electrical activity from the brain. Four distinct levels of green-red color diff...

Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space.

Sensors (Basel, Switzerland)
BACKGROUND AND OBJECTIVES: Depth perception of the human visual system in three-dimensional (3D) space plays an important role in human-computer interaction and artificial intelligence (AI) areas. It mainly employs binocular disparity and motion para...

No-reference stereoscopic image quality assessment based on binocular collaboration.

Neural networks : the official journal of the International Neural Network Society
Stereoscopic images typically consist of left and right views along with depth information. Assessing the quality of stereoscopic/3D images (SIQA) is often more complex than that of 2D images due to scene disparities between the left and right views ...

An artificial intelligence platform for the screening and managing of strabismus.

Eye (London, England)
OBJECTIVES: Considering the escalating incidence of strabismus and its consequential jeopardy to binocular vision, there is an imperative demand for expeditious and precise screening methods. This study was to develop an artificial intelligence (AI) ...

Research on the Industrial Robot Grasping Method Based on Multisensor Data Fusion and Binocular Vision.

Computational intelligence and neuroscience
At present, most of the handling industrial robots working on the production line are operated by teaching or preprogramming, which makes the flexibility of the production line poor and does not meet the flexible production requirements of the materi...

DeepFoveaNet: Deep Fovea Eagle-Eye Bioinspired Model to Detect Moving Objects.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Birds of prey especially eagles and hawks have a visual acuity two to five times better than humans. Among the peculiar characteristics of their biological vision are that they have two types of foveae; one shallow fovea used in their binocular visio...

Eye Gaze Based 3D Triangulation for Robotic Bionic Eyes.

Sensors (Basel, Switzerland)
Three-dimensional (3D) triangulation based on active binocular vision has increasing amounts of applications in computer vision and robotics. An active binocular vision system with non-fixed cameras needs to calibrate the stereo extrinsic parameters ...

Symmetry of generalized rivalry network models determines patterns of interocular grouping in four-location binocular rivalry.

Journal of neurophysiology
Previously, symmetry of network models has been proposed to account for interocular grouping during binocular rivalry. Here, we construct and analyze generalized rivalry network models with different types of symmetry (based on different kinds of exc...

Emergence of Binocular Disparity Selectivity through Hebbian Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Földiák, 1989;...