Computational intelligence and neuroscience
Dec 15, 2020
It is necessary to improve the performance of the object detection algorithm in resource-constrained embedded devices by lightweight improvement. In order to further improve the recognition accuracy of the algorithm for small target objects, this pap...
Smartphone-sensors-based human activity recognition is attracting increasing interest due to the popularization of smartphones. It is a difficult long-range temporal recognition problem, especially with large intraclass distances such as carrying sma...
Journal of experimental psychology. Learning, memory, and cognition
Nov 5, 2020
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), ...
We recently argued that human unfamiliar face identity perception reflects substantial perceptual expertise, and that the advantage for familiar over unfamiliar face identity matching reflects a learned mapping between generic high-level perceptual f...
To isolate brain activity that may reflect effective cognitive processes during the study phase of a memory task, cognitive neuroscientists commonly contrast brain activity during study of later-remembered versus later-forgotten items. This "subseque...
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Sep 28, 2020
OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavioral domains, including impairments of social communication and stereotyped behavior. Unlike typicall...
Advances in Deep Convolutional Neural Networks (DCNN) provide new opportunities for computational neuroscience to pose novel questions regarding the function of biological visual systems. Some attempts have been made to utilize advances in machine le...
Attractor neural networks such as the Hopfield model can be used to model associative memory. An efficient associative memory should be able to store a large number of patterns which must all be stable. We study in detail the meaning and definition o...
Neural networks : the official journal of the International Neural Network Society
Aug 17, 2020
Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion. Spiking neural networks (SNNs) represent a family of event-driven models...
The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutual understanding of each other's actions and intentions. In this paper, we motivate and present a sy...
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