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Lígia Conceição, Gonçalo Homem de Almeida Correia, Bart van Arem and José Pedro Tavares
Once trusted, automated vehicles (AVs) will gradually appear in urban areas. Such a transition is an opportunity in transport planning to control undesired impacts and possibly mitigate congestion at a time when both conventional vehicles (CVs) and AVs c...
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Antonello Pasini and Stefano Amendola
Neural network models are often used to analyse non-linear systems; here, in cases of small datasets, we review our complementary approach to deep learning with the purpose of highlighting the importance and roles (linear, non-linear or threshold) of cer...
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Xiaojuan Wang and Weilan Wang
As there is a lack of public mark samples of Tibetan historical document image characters at present, this paper proposes an unsupervised Tibetan historical document character recognition method based on deep learning (UD-CNN). Firstly, using the Tibetan...
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Zongshun Wang, Ce Li, Jialin Ma, Zhiqiang Feng and Limei Xiao
In this study, we introduce a novel framework for the semantic segmentation of point clouds in autonomous driving scenarios, termed PVI-Net. This framework uniquely integrates three different data perspectives?point clouds, voxels, and distance maps?exec...
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Weilai Jiang, Chenghong Zheng, Delong Hou, Kangsheng Wu and Yaonan Wang
The autonomous shape decision-making problem of a morphing aircraft (MA) with a variable wingspan and sweep angle is studied in this paper. Considering the continuity of state space and action space, a more practical autonomous decision-making algorithm ...
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