Neural networks : the official journal of the International Neural Network Society
May 12, 2021
Efficient learning of spikes plays a valuable role in training spiking neural networks (SNNs) to have desired responses to input stimuli. However, current learning rules are limited to a binary form of spikes. The seemingly ubiquitous phenomenon of b...
Neural networks : the official journal of the International Neural Network Society
May 8, 2021
Towards exploring the topological structure of data, numerous graph embedding clustering methods have been developed in recent years, none of them takes into account the cluster-specificity distribution of the nodes representations, resulting in subo...
International journal of computer assisted radiology and surgery
May 5, 2021
PURPOSE: Automatic workflow recognition from surgical videos is fundamental and significant for developing context-aware systems in modern operating rooms. Although many approaches have been proposed to tackle challenges in this complex task, there a...
Journal of neurophysiology
Apr 28, 2021
A common pitfall of current reinforcement learning agents implemented in computational models is in their inadaptability postoptimization. Najarro and Risi [Najarro E, Risi S. . 2020: 20719-20731, 2020] demonstrate how such adaptability may be salvag...
Nature communications
Apr 22, 2021
Cognitive maps are mental representations of spatial and conceptual relationships in an environment, and are critical for flexible behavior. To form these abstract maps, the hippocampus has to learn to separate or merge aliased observations appropria...
Neural networks : the official journal of the International Neural Network Society
Apr 21, 2021
Zero-shot learning (ZSL) aims to recognize objects in images when no training data is available for the object classes. Under generalized zero-shot learning (GZSL) setting, the test objects belong to seen or unseen categories. In many recent studies,...
Neural networks : the official journal of the International Neural Network Society
Apr 20, 2021
Existing convolution techniques in artificial neural networks suffer from huge computation complexity, while the biological neural network works in a much more powerful yet efficient way. Inspired by the biological plasticity of dendritic topology an...
Science bulletin
Apr 17, 2021
Spiking neural network, inspired by the human brain, consisting of spiking neurons and plastic synapses, is a promising solution for highly efficient data processing in neuromorphic computing. Recently, memristor-based neurons and synapses are becomi...
PloS one
Apr 15, 2021
The efficacy of evolutionary or reinforcement learning algorithms for continuous control optimization can be enhanced by including an additional neural network dedicated to features extraction trained through self-supervision. In this paper we introd...
Sensors (Basel, Switzerland)
Apr 13, 2021
Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artificial units of high biological plausibility. Adaptability is among the characteristics of such control units, which provides the anthropomorphic hand w...