A key challenge for systems neuroscience is to understand the coexistence of robustness and sensitivity in neural networks. In particular, a neural system must be robust against perturbations to its ...
Objects may appear at arbitrary scales in perspective images of a scene, posing a challenge for recognition systems that process an image at a fixed resolution. We propose a depth-aware gating module ...
Abstract: The paper presents an original contribution related to the implementation of a neural network artificial intelligence (AI) technique through Matlab environment, on the study of induced AC ...
Abstract: This article develops a recurrent neural network (RNN) with an encoder–decoder structure to predict the driving sequence of SiC MOSFET active gate drivers (AGDs). With a set of switching ...
Laboratory of Data Science and Digital Inclusion, Institut de Mathématiques et de Sciences Physiques, Université d’Abomey-Calavi, Abomey-Calavi, Bénin. Diabetes is a chronic disease. In 2019, it was ...
The currently applied maintenance strategies, including Reactive and Preventive maintenance can be considered obsolete. The constant improvements in Information and Communication Technologies as well ...
More than 70 years ago, researchers at the forefront of artificial intelligence research introduced neural networks as a revolutionary way to think about how the brain works. In the human brain, ...
Recent advances in artificial intelligence and deep learning have significantly improved the capability of recurrently connected artificial neural networks. Although these networks can achieve high ...
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