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Preschoolers' Motivation to Over-Imitate Humans and Robots.

Child development
From preschool age, humans tend to imitate causally irrelevant actions-they over-imitate. This study investigated whether children over-imitate even when they know a more efficient task solution and whether they imitate irrelevant actions equally fro...

Computational discrimination between natural images based on gaze during mental imagery.

Scientific reports
When retrieving image from memory, humans usually move their eyes spontaneously as if the image were in front of them. Such eye movements correlate strongly with the spatial layout of the recalled image content and function as memory cues facilitatin...

A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation Task-Driven CNNs.

Computational and mathematical methods in medicine
Nowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differe...

A hybrid unsupervised-Deep learning tandem for electrooculography time series analysis.

PloS one
Medical data are often tricky to get mined for patterns even by the generally demonstrated successful modern methodologies of deep learning. This paper puts forward such a medical classification task, where patient registers of two of the categories ...

The Effect of the Graphic Structures of Humanoid Robot on N200 and P300 Potentials.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Humanoid robots are widely used in brain computer interface (BCI). Using a humanoid robot stimulus could increase the amplitude of event-related potentials (ERPs), which improves BCI performance. Since a humanoid robot contains many human elements, t...

Feature fusion via Deep Random Forest for facial age estimation.

Neural networks : the official journal of the International Neural Network Society
In the last few years, human age estimation from face images attracted the attention of many researchers in computer vision and machine learning fields. This is due to its numerous applications. In this paper, we propose a new architecture for age es...

Appearance variation adaptation tracker using adversarial network.

Neural networks : the official journal of the International Neural Network Society
Visual trackers using deep neural networks have demonstrated favorable performance in object tracking. However, training a deep classification network using overlapped initial target regions may lead an overfitted model. To increase the model general...

A Modeling Study of the Emergence of Eye Position Gain Fields Modulating the Responses of Visual Neurons in the Brain.

Frontiers in neural circuits
The responses of many cortical neurons to visual stimuli are modulated by the position of the eye. This form of gain modulation by eye position does not change the retinotopic selectivity of the responses, but only changes the amplitude of the respon...

Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion.

Sensors (Basel, Switzerland)
The paper proposes a method of visual attention-based emotion classification through eye gaze analysis. Concretely, tensor-based emotional category classification via visual attention-based heterogeneous convolutional neural network (CNN) feature fus...

Crowding in humans is unlike that in convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Object recognition is a primary function of the human visual system. It has recently been claimed that the highly successful ability to recognise objects in a set of emergent computer vision systems-Deep Convolutional Neural Networks (DCNNs)-can form...