AIMC Topic: Vision, Ocular

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Unsupervised foveal vision neural architecture with top-down attention.

Neural networks : the official journal of the International Neural Network Society
Deep learning architectures are an extremely powerful tool for recognizing and classifying images. However, they require supervised learning and normally work on vectors of the size of image pixels and produce the best results when trained on million...

Limits to visual representational correspondence between convolutional neural networks and the human brain.

Nature communications
Convolutional neural networks (CNNs) are increasingly used to model human vision due to their high object categorization capabilities and general correspondence with human brain responses. Here we evaluate the performance of 14 different CNNs compare...

Generation of Tactile Data From 3D Vision and Target Robotic Grasps.

IEEE transactions on haptics
Tactile perception is a rich source of information for robotic grasping: it allows a robot to identify a grasped object and assess the stability of a grasp, among other things. However, the tactile sensor must come into contact with the target object...

One-shot object parsing in newborn chicks.

Journal of experimental psychology. General
Controlled-rearing studies provide the unique opportunity to examine which psychological mechanisms are present at birth and which mechanisms emerge from experience. Here we show that one core component of visual perception-the ability to parse objec...

Bioinspired multisensory neural network with crossmodal integration and recognition.

Nature communications
The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation...

Deep learning-based pupil model predicts time and spectral dependent light responses.

Scientific reports
Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State o...

Going in circles is the way forward: the role of recurrence in visual inference.

Current opinion in neurobiology
Biological visual systems exhibit abundant recurrent connectivity. State-of-the-art neural network models for visual recognition, by contrast, rely heavily or exclusively on feedforward computation. Any finite-time recurrent neural network (RNN) can ...

Predicting risk of dyslexia with an online gamified test.

PloS one
Dyslexia is a specific learning disorder related to school failure. Detection is both crucial and challenging, especially in languages with transparent orthographies, such as Spanish. To make detecting dyslexia easier, we designed an online gamified ...

An Accelerated Finite-Time Convergent Neural Network for Visual Servoing of a Flexible Surgical Endoscope With Physical and RCM Constraints.

IEEE transactions on neural networks and learning systems
This article designs and analyzes a recurrent neural network (RNN) for the visual servoing of a flexible surgical endoscope. The flexible surgical endoscope is based on a commercially available UR5 robot with a flexible endoscope attached as an end-e...

3D shape estimation in a constraint optimization neural network.

Vision research
One of the most important aspects of visual perception is the inference of 3D shape from a 2D retinal image of the outside world. The existence of several valid mapping functions from object to data makes this inverse problem ill-posed and therefore ...