AIMC Topic: Photic Stimulation
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Feature fusion via Deep Random Forest for facial age estimation.
Neural networks : the official journal of the International Neural Network Society
Jul 14, 2020
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
Jun 17, 2020
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
May 26, 2020
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)
Apr 10, 2020
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
Mar 27, 2020
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...
Learning visual features under motion invariance.
Neural networks : the official journal of the International Neural Network Society
Mar 20, 2020
Humans are continuously exposed to a stream of visual data with a natural temporal structure. However, most successful computer vision algorithms work at image level, completely discarding the precious information carried by motion. In this paper, we...
Cross-modal dual subspace learning with adversarial network.
Neural networks : the official journal of the International Neural Network Society
Mar 19, 2020
Cross-modal retrieval has recently attracted much interest along with the rapid development of multimodal data, and effectively utilizing the complementary relationship of different modal data and eliminating the heterogeneous gap as much as possible...
Causal importance of low-level feature selectivity for generalization in image recognition.
Neural networks : the official journal of the International Neural Network Society
Feb 24, 2020
Although our brain and deep neural networks (DNNs) can perform high-level sensory-perception tasks, such as image or speech recognition, the inner mechanism of these hierarchical information-processing systems is poorly understood in both neuroscienc...
A neural circuit model for a contextual association task inspired by recommender systems.
Hippocampus
Feb 14, 2020
Behavioral data shows that humans and animals have the capacity to learn rules of associations applied to specific examples, and generalize these rules to a broad variety of contexts. This article focuses on neural circuit mechanisms to perform a con...
Separability and geometry of object manifolds in deep neural networks.
Nature communications
Feb 6, 2020
Stimuli are represented in the brain by the collective population responses of sensory neurons, and an object presented under varying conditions gives rise to a collection of neural population responses called an 'object manifold'. Changes in the obj...
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