Design of neural networks for classification of remotely sensed imagery [PDF]
Classification accuracies of a backpropagation neural network are discussed and compared with a maximum likelihood classifier (MLC) with multivariate normal class models.
Birmingham, Mark +2 more
core +1 more source
ANOMALY NETWORK INTRUSION DETECTION SYSTEM BASED ON DISTRIBUTED TIME-DELAY NEURAL NETWORK (DTDNN) [PDF]
Journal of Engineering Science and Technology, 2010 In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS,
LAHEEB MOHAMMAD IBRAHIM
doaj
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
core +1 more source
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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Integration of perception and reasoning in fast neural modules [PDF]
Artificial neural systems promise to integrate symbolic and sub-symbolic processing to achieve real time control of physical systems. Two potential alternatives exist. In one, neural nets can be used to front-end expert systems.
Fritz, David G.
core +1 more source
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
doaj +1 more source
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
doaj +1 more source