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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Xiankun Zhang,Yijie Pan Conference proceed

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樓主: Addiction
41#
發(fā)表于 2025-3-28 16:33:40 | 只看該作者
An Optimization Method Based on Drift Data and Time Series Information. Compared with traditional static data, streaming data typically exhibits the phenomenon of concept drift. This makes it challenging for traditional machine learning methods to uncover the potential application value of streaming data. To solve this problem, previous literature has proposed various
42#
發(fā)表于 2025-3-28 20:31:44 | 只看該作者
IG-GRD: A Model Based on Disentangled Graph Representation Learning for Imaging Genetic Data Fusionlications for the early diagnosis of Alzheimer’s Disease (AD) and the exploration of its underlying mechanisms. Current fusion methods focus primarily on the correlation between modalities or rely on decision-level fusion. However, due to the heterogeneity of imaging and genetic data, as well as the
43#
發(fā)表于 2025-3-28 23:50:37 | 只看該作者
Automatic Meibomian Gland Segmentation and Assessment Based on TransUnet with Data Augmentationtechnology, non-contact infrared imaging named meibography has become mainstream. Physicians determine the meiboscore based on meibography images, which serves for the follow-up diagnosis. In this paper, a deep learning-based MG segmentation approach has been proposed to accurately segment meibograp
44#
發(fā)表于 2025-3-29 06:49:09 | 只看該作者
45#
發(fā)表于 2025-3-29 10:35:16 | 只看該作者
46#
發(fā)表于 2025-3-29 11:52:34 | 只看該作者
Surrogate-Assisted Evolutionary Neural Architecture Search with Isomorphic Training and Predictioniated with a significant computational cost. Surrogate models, which predict the performance of candidate networks without training them, are thus used to speed up NAS calculations. Since surrogate models must be trained, their performance depends on the dataset of labelled candidate architectures.
47#
發(fā)表于 2025-3-29 16:02:36 | 只看該作者
Explainable Deep Learning with Human Feedback for Perioperative Complications Predictionrinatal complications, greatly endangering the health of pregnant women and their newborns. Timely identification, provision of relevant resources, and timely response are the key to preventing serious complications and mortality in delivery women. The current predictive models used in medicine have
48#
發(fā)表于 2025-3-29 22:25:17 | 只看該作者
0302-9743 applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology..978-981-97-5580-6978-981-97-5581-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
49#
發(fā)表于 2025-3-30 00:29:40 | 只看該作者
50#
發(fā)表于 2025-3-30 05:43:12 | 只看該作者
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