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Mingyoung Jeng, Alvir Nobel, Vinayak Jha, David Levy, Dylan Kneidel, Manu Chaudhary, Ishraq Islam, Evan Baumgartner, Eade Vanderhoof, Audrey Facer, Manish Singh, Abina Arshad and Esam El-Araby
Convolutional neural networks (CNNs) have proven to be a very efficient class of machine learning (ML) architectures for handling multidimensional data by maintaining data locality, especially in the field of computer vision. Data pooling, a major compon...
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Yuntao Shi, Hongfei Zhang, Wei Guo, Meng Zhou, Shuqin Li, Jie Li and Yu Ding
This research proposes a face detection algorithm named LighterFace, which is aimed at enhancing detection speed to meet the demands of real-time community applications. Two pre-trained convolutional neural networks are combined, namely Cross Stage Parti...
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Hassen Louati, Ali Louati, Rahma Lahyani, Elham Kariri and Abdullah Albanyan
Responding to the critical health crisis triggered by respiratory illnesses, notably COVID-19, this study introduces an innovative and resource-conscious methodology for analyzing chest X-ray images. We unveil a cutting-edge technique that marries neural...
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Chunling Wang, Tianyi Hang, Changke Zhu and Qi Zhang
The Czech Republic is one of the countries along the Belt and Road Initiative, and classifying land cover in the Czech Republic helps to understand the distribution of its forest resources, laying the foundation for forestry cooperation between China and...
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Artemiy Belousov, Ivan Kisel, Robin Lakos and Akhil Mithran
Algorithms optimized for high-performance computing, which ensure both speed and accuracy, are crucial for real-time data analysis in heavy-ion physics experiments. The application of neural networks and other machine learning methodologies, which are fa...
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