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Full-Text Articles in Physical Sciences and Mathematics
A Multi-Branch Separable Convolution Neural Network For Pedestrian Attribute Recognition, Imran N. Junejo, Naveed Ahmed
A Multi-Branch Separable Convolution Neural Network For Pedestrian Attribute Recognition, Imran N. Junejo, Naveed Ahmed
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© 2020 The Authors Computer science; Computer Vision; Image processing; Deep learning; Pedestrian attribute recognition
Ai Techniques For Covid-19, Adedoyin Ahmed Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily
Ai Techniques For Covid-19, Adedoyin Ahmed Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily
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© 2013 IEEE. Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the …
Improving M-Learners' Performance Through Deep Learning Techniques By Leveraging Features Weights, Muhammad Adnan, Asad Habib, Jawad Ashraf, Babar Shah, Gohar Ali
Improving M-Learners' Performance Through Deep Learning Techniques By Leveraging Features Weights, Muhammad Adnan, Asad Habib, Jawad Ashraf, Babar Shah, Gohar Ali
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© 2013 IEEE. Mobile learning (M-learning) has gained tremendous attention in the educational environment in the past decade. For effective M-learning, it is important to create an efficient M-learning model that can identify the exact requirements of mobile learners (M-learners). M-learning model is composed of features that are generated during M-learners' interaction with mobile devices. For an adaptive M-learning model, not only learning features are required, but it is also important to determine how they differ for various M-learners, their weights, and interrelationship. This study proposes a robust and adaptive M-learning model that is based on machine learning and deep …