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Investigation of Energy-Efficient AI Model Architectures and Compression Techniques for “Green” Fetal Brain Segmentation
Artificial intelligence has contributed to advancements across various industries. However, the rapid growth of artificial intelligence technologies also raises concerns about their environmental impact, due to associated carbon footprints to train computational...
However, the rapid growth of artificial intelligence technologies also raises concerns about their environmental impact, due to associated carbon footprints to train computational models. Our findings demonstrate that these methods lead to satisfactory model performance with the low energy consumption during deep neural network training for medical image segmentation. Ciceri, T., Squarcina, L., Giubergia, A., Bertoldo, A., Brambilla, P., Peruzzo, D.: Review on deep learning fetal brain segmentation from magnetic resonance images.
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