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Jingying Zhang and Tengfei Bao
Crack detection is an important component of dam safety monitoring. Detection methods based on deep convolutional neural networks (DCNNs) are widely used for their high efficiency and safety. Most existing DCNNs with high accuracy are too complex for use...
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Goutham Kallempudi, Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker and Muhammad Zeshan Afzal
The graphical page object detection classifies and localizes objects such as Tables and Figures in a document. As deep learning techniques for object detection become increasingly successful, many supervised deep neural network-based methods have been in...
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Zhou Lei, Kangkang Yang, Kai Jiang and Shengbo Chen
Person re-Identification(Re-ID) based on deep convolutional neural networks (CNNs) achieves remarkable success with its fast speed. However, prevailing Re-ID models are usually built upon backbones that manually design for classification. In order to aut...
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María Soledad Ramírez-Montoya, María Isabel Loaiza-Aguirre, Alexandra Zúñiga-Ojeda and May Portuguez-Castro
The authors of the Education 4.0 concept postulated a flexible combination of digital literacy, critical thinking, and problem-solving in educational environments linked to real-world scenarios. Therefore, teachers have been challenged to develop new met...
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Linda Lucia Esquivel Trujillo,Juan Pablo Orejuela C
Pág. 20 - 29
Esta investigación aborda el problema de programación del horario escolar en Instituciones Educativas, con dos jornadas y con múltiples sedes, que exigen el desplazamiento de algunos maestros entre estas. El problema se resuelve mediante un modelo de pro...
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Johanna G. Ferreira
Pág. 5 bladsye
The purpose of this article was to investigate the extent to which technology can be used in the training of teachers at a distance to prepare them comprehensively for their careers. Because the so called soft skills and associated character traits ...
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