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Hyeong-Ju Kang
Object detection in many real applications requires the capability of detecting small objects in a system with limited resources. Convolutional neural networks (CNNs) show high performance in object detection, but they are not adequate to resource-limite...
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Kang Niu, Xu Bai, Xi Chen, Di Yang, Jiaxun Li and Jianqiao Yu
To improve the performance of intercepting a target with different maneuvering modes and changing the mode suddenly during the interception, a new adaptive control algorithm for the IGC (Integrated Guidance and Control) system is proposed, using the glob...
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Felipe C. Farias, Teresa B. Ludermir and Carmelo J. A. Bastos-Filho
In this paper we propose a procedure to enable the training of several independent Multilayer Perceptron Neural Networks with a different number of neurons and activation functions in parallel (ParallelMLPs) by exploring the principle of locality and par...
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Slawomir Czarnecki, Adrian Chajec, Seweryn Malazdrewicz and Lukasz Sadowski
This paper predicts the abrasion resistance of a cementitious composite containing granite powder and fly ash replacing up to 30% of the cement weight. For this purpose, intelligent artificial neural network (ANN) models were used and compared. A databas...
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Wei Gao, Mengxue Han, Zhao Wang, Lihui Deng, Hongjian Wang and Jingfei Ren
A UUV can perform tasks such as underwater surveillance, reconnaissance, surveillance, and tracking by being equipped with sensors and different task modules. Due to the complex underwater environment, the UUV must have good collision avoidance planning ...
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