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Titlebook: Applied Intelligence and Informatics; Second International Mufti Mahmud,Cosimo Ieracitano,Francesco Carlo Mor Conference proceedings 2022 T

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樓主: 搖尾乞憐
31#
發(fā)表于 2025-3-26 23:25:27 | 只看該作者
32#
發(fā)表于 2025-3-27 03:22:11 | 只看該作者
Nezameddin Faghih,Mohammad Reza Zaliictive models will help to indicate the seriousness of the patients and assist the doctors in taking immediate actions. The Medical Information Mart for Intensive Care III (MIMIC-III) dataset is used in this research. The medicines medicated in critical newborn children were detected, and how the dr
33#
發(fā)表于 2025-3-27 09:15:08 | 只看該作者
34#
發(fā)表于 2025-3-27 11:33:26 | 只看該作者
Shahamak Rezaei,Victoria Hill,Yipeng Liuto its ability to rapid learning of end-to-end models accurately using compound data. Recent years have seen an extensive application of Deep Learning (DL) models in solving the 4-way classification of Alzheimer’s Disease (AD) and achieved good results too. However, traditional machine learning clas
35#
發(fā)表于 2025-3-27 13:46:30 | 只看該作者
Ali Davari,Amer Dehghan Najmabadiasurement of the Crown to Rump Length (CRL), it is a crucial scan as it informs obstetric practitioners of the optimal timing for any necessary interventions at the earliest point. Inter-observer variation creates problems for Obstetric Practitioners as any variation in the measurement of the CRL ca
36#
發(fā)表于 2025-3-27 21:42:16 | 只看該作者
Applied Intelligence and Informatics978-3-031-24801-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
37#
發(fā)表于 2025-3-27 22:15:07 | 只看該作者
38#
發(fā)表于 2025-3-28 04:05:48 | 只看該作者
MEMS and AI for the Recognition of Human Activities on IoT Platformses or nursing homes. Finally, to determine the position of subjects, we associate the prototype with a positioning system on the ultrasonic platform. Finally, applying the Edge Machine Learning technique, we developed an application on the STM32L475VG microprocessor on which motion acquisition and a
39#
發(fā)表于 2025-3-28 08:30:35 | 只看該作者
Tackling the?Linear Sum Assignment Problem with?Graph Neural Networksfor a significant increase in classification accuracy if compared with two different DNN approaches based on Dense Networks and Convolutional Neural Networks, furthermore, the GNN has proved to be very efficient with regard to the processing time and memory requirements, thanks to intrinsic paramete
40#
發(fā)表于 2025-3-28 13:04:33 | 只看該作者
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