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Titlebook: Advances in Computing and Network Communications; Proceedings of CoCoN Sabu M. Thampi,Erol Gelenbe,Kuan-Ching Li Conference proceedings 202

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發(fā)表于 2025-3-23 13:20:23 | 只看該作者
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發(fā)表于 2025-3-23 17:36:51 | 只看該作者
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發(fā)表于 2025-3-23 20:20:12 | 只看該作者
1876-1100 cial Intelligence and?Cognitive Computing and Circuits and Systems. The book is directed to the researchers and scientists engaged in?various fields of computing and network communication domains..978-981-33-6989-4978-981-33-6987-0Series ISSN 1876-1100 Series E-ISSN 1876-1119
14#
發(fā)表于 2025-3-24 00:26:45 | 只看該作者
The Developing Public Sector Perspective,piking activity and conductive properties of the extracellular medium to the LFP. The computation study reproduces experimentally observed in vitro N2a and N2b evoked LFP waves and can be used to test the scaling of models developed from a bottom-up approach.
15#
發(fā)表于 2025-3-24 03:13:24 | 只看該作者
Fabiana Roberto,Roberto Maglio,Andrea Reyed on each block to extract the unique iris code as the feature vector. The experiments have been conducted using the multimodal biometric database, SDUMLA-HMT. The proposed system has succeeded in achieving a low false acceptance rate and a very low false rejection rate. Also, the uniqueness of the
16#
發(fā)表于 2025-3-24 07:26:30 | 只看該作者
17#
發(fā)表于 2025-3-24 13:13:31 | 只看該作者
Jean-Pierre Wils,Ruth Baumann-H?lzle we intended to develop a microbiome dataset with all the relevant concepts tagged for training a NER model which is to be a part of a semantic information retrieval tool. For this, we engineered a dataset specifically focusing on keywords related to the characteristics of the wastewater microbiomet
18#
發(fā)表于 2025-3-24 15:24:29 | 只看該作者
Integration ist keine Einbahnstra?e positive cases from a mass collection. Radiological imaging like computed tomography (CT) scans can be used for the early diagnosis. With the invention of AI algorithms, we can apply learning algorithms for early detection of COVID-19. 2016 on wards, deep learning, a deep neural network-based learn
19#
發(fā)表于 2025-3-24 19:57:00 | 只看該作者
https://doi.org/10.1007/978-3-662-55937-6ertiary structures from primary sequences. The result shows that single-layer BLSTM networks fed with primary sequence and position-specific scoring matrix data gives better accuracy compared to LSTM and two-layer BLSTM models. This study may get benefited to the computational biologists working in
20#
發(fā)表于 2025-3-25 02:15:50 | 只看該作者
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