Few‐label aerial target intention recognition based on self‐supervised contrastive learning
IET Radar, Sonar & NavigationIdentifying the intentions of aerial targets is crucial for air situation understanding and decision making. Deep learning, with its powerful feature learning and representation capability, has become a key means to achieve higher performance in aerial ...
Zihao Song +5 more
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Third Conference on Artificial Intelligence for Space Applications, part 2 [PDF]
Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are ...
Denton, Judith S. +2 more
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Recognition of European mammals and birds in camera trap images using deep neural networks
IET Computer VisionMost machine learning methods for animal recognition in camera trap images are limited to mammal identification and group birds into a single class. Machine learning methods for visually discriminating birds, in turn, cannot discriminate between mammals ...
Daniel Schneider +5 more
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The use of artificial neural networks in experimental data acquisition and aerodynamic design [PDF]
It is proposed that an artificial neural network be used to construct an intelligent data acquisition system. The artificial neural networks (ANN) model has a potential for replacing traditional procedures as well as for use in computational fluid ...
Meade, Andrew J., Jr.
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Daily average load demand forecasting using LSTM model based on historical load trends
IET Generation, Transmission & DistributionLoad demand forecasting is very important for the management, designing and analysis of an electrical grid system. Load forecasting has progressively become a crucial component of the energy management system with the growth of the smart micro grid. This
Rashmi Bareth +3 more
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Spike-Train Level Direct Feedback Alignment: Sidestepping Backpropagation for On-Chip Training of Spiking Neural Nets. [PDF]
Front Neurosci, 2020 Lee J, Zhang R, Zhang W, Liu Y, Li P.
europepmc +1 more source
Person re‐identification via deep compound eye network and pose repair module
IET Computer VisionPerson re‐identification is aimed at searching for specific target pedestrians from non‐intersecting cameras. However, in real complex scenes, pedestrians are easily obscured, which makes the target pedestrian search task time‐consuming and challenging ...
Hongjian Gu +5 more
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An image inpainting method based on generative adversarial networks inversion and autoencoder
IET Image ProcessingImage inpainting aims to repair the damaged region according to the known content in the damaged image. Recently, image inpainting methods have poor effects on high‐resolution damaged images, and the research on the inpainting of large‐area damaged ...
Yechen Wang, Bin Song, Zhiyong Zhang
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Segmentation‐enhanced gamma spectrum denoising based on deep learning
IET CommunicationsGamma spectrum denoising can reduce the adverse effects of statistical fluctuations of radioactivity, gamma ray scattering, and electronic noise on the measured gamma spectrum.
Xiangqun Lu +6 more
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Научно-технический вестник информационных технологий, механики и оптики, 2007 Научный руководитель С.А. Ермолаева. В статье рассматриваются некоторые наиболее интересные свойства современных нейронных сетей, их устройство и характеристики. Также приведена краткая история появления современных методов искусственного интеллекта, моделирующих деятельность человеческого мозга.
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