Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2020; 21st International C Cesar Analide,Paulo Novais,Hujun Yin Conference proc

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A Comparison of Evolutionary Multi-objective Optimization Algorithms Applied to Antenna Designamong all output variables. Multi-objective optimization algorithms are promising candidates for providing Pareto Fronts that describe these possibilities. Particularly in antenna design, the input variables are geometrical elements associated with the antenna type. On the other hand, the output var

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Cloud Type Identification Using Data Fusion and Ensemble Learnings. However, many properties of this domain make high classification accuracy difficult to achieve. In this paper, we design a novel fusion approach, showing that recent image classification architectures based on deep learning, such as Convolutional Neural Networks, can be improved using statistical

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Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reportsnautic enterprises and regulators. In this sense, a concept known as Single Pilot Operations arises in the task of dealing with these challenges, for which, automation becomes necessary, especially in Air Traffic Management. In this regard, this paper presents a deep learning-based approach to lever

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Analysis of Hand-Crafted and Automatic-Learned Features for Glaucoma Detection Through Raw Circumpapucoma detection in order to elucidate that traditional machine-learning techniques could outperform deep-learning algorithms, especially when the image data set is small. The experiments were performed on a private database composed of 194 glaucomatous and 198 normal B-scans diagnosed by expert opht

高深莫測

Video Semantics Quality Assessment Using Deep Learningtic information extracted from videos and the information obtained from text news of the same event. Deep learning techniques are used to detect objects in the video scenes. News articles are represented by a set of relevant terms automatically extracted from the news. This paper describes our metho

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