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Visual Perception

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Transfer of Learning from Vision to Touch: A Hybrid Deep Convolutional Neural Network for Visuo-Tactile 3D Object Recognition.

Sensors (Basel, Switzerland)
Transfer of learning or leveraging a pre-trained network and fine-tuning it to perform new tasks has been successfully applied in a variety of machine intelligence fields, including computer vision, natural language processing and audio/speech recogn...

Transforming task representations to perform novel tasks.

Proceedings of the National Academy of Sciences of the United States of America
An important aspect of intelligence is the ability to adapt to a novel task without any direct experience (zero shot), based on its relationship to previous tasks. Humans can exhibit this cognitive flexibility. By contrast, models that achieve superh...

A comprehensive study of class incremental learning algorithms for visual tasks.

Neural networks : the official journal of the International Neural Network Society
The ability of artificial agents to increment their capabilities when confronted with new data is an open challenge in artificial intelligence. The main challenge faced in such cases is catastrophic forgetting, i.e., the tendency of neural networks t...

Artificial fly visual joint perception neural network inspired by multiple-regional collision detection.

Neural networks : the official journal of the International Neural Network Society
The biological visual system includes multiple types of motion sensitive neurons which preferentially respond to specific perceptual regions. However, it still keeps open how to borrow such neurons to construct bio-inspired computational models for m...

A brain-inspired network architecture for cost-efficient object recognition in shallow hierarchical neural networks.

Neural networks : the official journal of the International Neural Network Society
The brain successfully performs visual object recognition with a limited number of hierarchical networks that are much shallower than artificial deep neural networks (DNNs) that perform similar tasks. Here, we show that long-range horizontal connecti...

Emotion Elicitation Under Audiovisual Stimuli Reception: Should Artificial Intelligence Consider the Gender Perspective?

International journal of environmental research and public health
Identification of emotions triggered by different sourced stimuli can be applied to automatic systems that help, relieve or protect vulnerable groups of population. The selection of the best stimuli allows to train these artificial intelligence-based...

Image memorability is predicted by discriminability and similarity in different stages of a convolutional neural network.

Learning & memory (Cold Spring Harbor, N.Y.)
The features of an image can be represented at multiple levels-from its low-level visual properties to high-level meaning. What drives some images to be memorable while others are forgettable? We address this question across two behavioral experiment...

DMMAN: A two-stage audio-visual fusion framework for sound separation and event localization.

Neural networks : the official journal of the International Neural Network Society
Videos are used widely as the media platforms for human beings to touch the physical change of the world. However, we always receive the mixed sound from the multiple sound objects, and cannot distinguish and localize the sounds as the separate entit...

Combining convolutional neural networks and cognitive models to predict novel object recognition in humans.

Journal of experimental psychology. Learning, memory, and cognition
Object representations from convolutional neural network (CNN) models of computer vision (LeCun, Bengio, & Hinton, 2015) were used to drive a cognitive model of decision making, the linear ballistic accumulator (LBA) model (Brown & Heathcote, 2008), ...

Performance vs. competence in human-machine comparisons.

Proceedings of the National Academy of Sciences of the United States of America
Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach "human-level" accuracy in an astounding variety of domains, and even predict human brain activity-raising the exciting possibil...