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Monika Rybczak and Krystian Kozakiewicz
Today, specific convolution neural network (CNN) models assigned to specific tasks are often used. In this article, the authors explored three models: MobileNet, EfficientNetB0, and InceptionV3 combined. The authors were interested in investigating how q...
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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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Guillaume Devic, Gilles Sassatelli and Abdoulaye Gamatié
The execution of machine learning (ML) algorithms on resource-constrained embedded systems is very challenging in edge computing. To address this issue, ML accelerators are among the most efficient solutions. They are the result of aggressive architectur...
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Yixian Fu, Yuanyao Lu and Ran Ni
Lip reading has attracted increasing attention recently due to advances in deep learning. However, most research targets English datasets. The study of Chinese lip-reading technology is still in its initial stage. Firstly, in this paper, we expand the na...
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Samuel Molcan, Monika Smie?ková, Hynek Bachratý, Katarína Bachratá and Peter Novotný
The elasticity of red blood cells (RBCs) plays a vital role in their efficient movement through blood vessels, facilitating the transportation of oxygen within the bloodstream. However, various diseases significantly impact RBC elasticity, making it an i...
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