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Ashokkumar Palanivinayagam and Robertas Dama?evicius
The existence of missing values reduces the amount of knowledge learned by the machine learning models in the training stage thus affecting the classification accuracy negatively. To address this challenge, we introduce the use of Support Vector Machine ...
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Jubilee Prasad-Rao, Olivia J. Pinon Fischer, Neil C. Rowe, Jesse R. Williams, Tejas G. Puranik, Dimitri N. Mavris, Michael W. Natali, Mitchell J. Tindall and Beth W. Atkinson
The cost to train a basic qualified U.S. Navy fighter aircraft pilot is nearly USD 10 M. The training includes primary, intermediate, and advanced stages, with the advanced stage involving extensive flight training, and, thus, is very expensive as a resu...
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Xulong Yu, Qiancheng Yu, Qunyue Mu, Zhiyong Hu and Jincai Xie
Traditional manual visual detection methods are inefficient, subjective, and costly, making them prone to false and missed detections. Deep-learning-based defect detection identifies the types of defects and pinpoints their locations. By employing this a...
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Jinxiu Zhao, Li Su, Xiangyu Wang, Jinjian Li, Fan Yang, Na Jiang and Quan Hu
The event camera, a new bio-inspired vision sensor with low latency and high temporal resolution, has brought great potential and demonstrated a promising application in machine vision and artificial intelligence. Corner detection is a key step of object...
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Seokwon Yeom and In-Jun Cho
Small unmanned aircraft vehicles (SUAVs) or drones are very useful for visual detection and tracking due to their efficiency in capturing scenes. This paper addresses the detection and tracking of moving pedestrians with an SUAV. The detection step consi...
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Martin Güthle, Jochen Kögel, Stefan Wahl, Matthias Kaschub and Christian M. Mueller
Service platforms using text-based protocols need to be protected against attacks. Machine-learning algorithms with pattern matching can be used to detect even previously unknown attacks. In this paper, we present an extension to known Support Vector Mac...
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