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Articles by Antonio Neme
Semi-Supervised Training for (Pre-Stack) Seismic Data Analysis
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A New Method for Classifying Scenes for Simultaneous Localization and Mapping Using the Boundary Object Function Descriptor on RGB-D Points
2. Related Work Scene classification using RGB-D cameras is an active area of research in robotics and computer vision. In this section, we provide an overview of the related work in this field as well as a panoramic view of the state of the art. Traditional image classification methods such as ORB or SIFT have been used for scene classification in SLAM systems. These methods rely on 2D image features and may not be sufficient for classifying 3D scenes accurately.
Mapping the citation network on vitamin D research in Australia: a data-driven approach
1 Introduction Vitamin D is a fat-soluble vitamin that is essential for bone health. Vitamin D can be obtained from various sources such as ultraviolet-B (UVB) radiation from sun exposure, dietary intake of foods that contain vitamin D (e.g., fish, eggs, and meat), and supplements (1, 2). There are two major forms of vitamin D, vitamin D3 (cholecalciferol), which can be obtained via sun exposure and dietary sources, and vitamin D2 (ergocalciferol), obtained from dietary sources.
DEJKMDR: miRNA-disease association prediction method based on graph convolutional network
Shiyuan Gao1 Zhufang Kuang1* Tao Duan1 Lei Deng2 1School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, China 2School of Computer Science and Engineering, Central South University, Changsha, China Numerous studies have shown that miRNAs play a crucial role in the investigation of complex human diseases. Identifying the connection between miRNAs and diseases is crucial for advancing the treatment of complex diseases.
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