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Mehdi Sadi, Bashir Mohammad Sabquat Bahar Talukder, Kaniz Mishty and Md Tauhidur Rahman
Universal adversarial perturbations are image-agnostic and model-independent noise that, when added to any image, can mislead the trained deep convolutional neural networks into the wrong prediction. Since these universal adversarial perturbations can se...
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Emmanouil Koutoulakis, Louis Marage, Emmanouil Markodimitrakis, Leone Aubignac, Catherine Jenny, Igor Bessieres and Alain Lalande
MR-Linac is a recent device combining a linear accelerator with an MRI scanner. The improved soft tissue contrast of MR images is used for optimum delineation of tumors or organs at risk (OARs) and precise treatment delivery. Automatic segmentation of OA...
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Eduardo Assunção, Pedro D. Gaspar, Khadijeh Alibabaei, Maria P. Simões, Hugo Proença, Vasco N. G. J. Soares and João M. L. P. Caldeira
Within the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applic...
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Arghavan Asad, Rupinder Kaur and Farah Mohammadi
From self-driving cars to detecting cancer, the applications of modern artificial intelligence (AI) rely primarily on deep neural networks (DNNs). Given raw sensory data, DNNs are able to extract high-level features after the network has been trained usi...
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Seungtae Hong, Hyunwoo Cho and Jeong-Si Kim
As embedded systems, such as smartphones with limited resources, have become increasingly popular, active research has recently been conducted on performing on-device deep learning in such systems. Therefore, in this study, we propose a deep learning fra...
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Yakun Wu, Li Luo, Shujuan Yin, Mengqi Yu, Fei Qiao, Hongzhi Huang, Xuesong Shi, Qi Wei and Xinjun Liu
The Simultaneous Localization and Mapping (SLAM) algorithm is a hotspot in robot application research with the ability to help mobile robots solve the most fundamental problems of ?localization? and ?mapping?. The visual semantic SLAM algorithm fused wit...
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Alexander Scheinker
Machine learning (ML) is growing in popularity for various particle accelerator applications including anomaly detection such as faulty beam position monitor or RF fault identification, for non-invasive diagnostics, and for creating surrogate models. ML ...
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Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Muhammad Shafique, Guido Masera and Maurizio Martina
Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial Intelligence (AI) applications. Their ability to go beyond human precision has made these networks a milestone in the history of AI. However, while on the one hand they ...
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Wan-Ju Lin, Shih-Hsuan Lo, Hong-Tsu Young and Che-Lun Hung
The use of surface roughness (Ra) to indicate product quality in the milling process in an intelligent monitoring system applied in-process has been developing. From the considerations of convenient installation and cost-effectiveness, accelerator vibrat...
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