In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and less time consuming are important. In this work, classification of abnormal location in switchgears is proposed using hybrid gravitational search alg...
Food research international (Ottawa, Ont.)
Jun 30, 2021
Clostridium sporogenes spores are used as surrogates for Clostridium botulinum, to verify thermal exposure and lethality in sterilization regimes by food industries. Conventional methods to detect spores are time-consuming and labour intensive. The o...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jun 30, 2021
The external pallidum (globus pallidus pars externa [GPe]) plays a central role for basal ganglia functions and dynamics and, consequently, has been included in most computational studies of the basal ganglia. These studies considered the GPe as a ho...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jun 30, 2021
Distributed population codes are ubiquitous in the brain and pose a challenge to downstream neurons that must learn an appropriate readout. Here we explore the possibility that this learning problem is simplified through inductive biases implemented ...
The main challenges for the automatic detection of the coronavirus disease (COVID-19) from computed tomography (CT) scans of an individual are: a lack of large datasets, ambiguity in the characteristics of COVID-19 and the detection techniques having...
Fourier transform infrared spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. W...
Separating and labeling each nuclear instance (instance-aware segmentation) is the key challenge in nuclear image segmentation. Deep Convolutional Neural Networks have been demonstrated to solve nuclear image segmentation tasks across different imagi...
Super-resolution (SR) methods have seen significant advances thanks to the development of convolutional neural networks (CNNs). CNNs have been successfully employed to improve the quality of endomicroscopy imaging. Yet, the inherent limitation of res...
Edge-cloud collaborative inference can significantly reduce the delay of a deep neural network (DNN) by dividing the network between mobile edge and cloud. However, the in-layer data size of DNN is usually larger than the original data, so the commun...
Loop Closure Detection (LCD) is an important technique to improve the accuracy of Simultaneous Localization and Mapping (SLAM). In this paper, we propose an LCD algorithm based on binary classification for feature matching between similar images with...
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