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Titlebook: Ubiquitous Intelligent Systems; Proceedings of Secon P. Karuppusamy,Fausto Pedro García Márquez,Tu N. N Conference proceedings 2022 The Edi

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樓主: 夸大
31#
發(fā)表于 2025-3-26 22:59:06 | 只看該作者
32#
發(fā)表于 2025-3-27 02:15:26 | 只看該作者
Fabric Defect Detection Using Deep Learning Techniques,eep learning techniques mainly Convolutional Neural Networks (CNN) has been developed. In this presented research, various optimizers are used, and the performance has been evaluated by using the fabric dataset called ZJU-Leaper. The proposed work provides an improved efficiency of 97.40% using ADAM optimizer.
33#
發(fā)表于 2025-3-27 07:02:57 | 只看該作者
A Review Paper on Machine Learning Techniques and Its Applications in Health Care Sector, techniques and advanced algorithms.?For analysis ML utilizes different algorithms such as Reinforcement Learning, Supervised Learning, and Unsupervised Learning. This paper discusses the Machine learning algorithms of many forms that can be used to analyse and survey enormous volumes of healthcare data.
34#
發(fā)表于 2025-3-27 13:31:08 | 只看該作者
35#
發(fā)表于 2025-3-27 17:25:39 | 只看該作者
Development of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology,d to prevent slow adaptive Byzantine malicious validators. Contrary to other sharding blockchains that require Proof-of-Work to select validators, the proposed consensus is attributed to Proof-of-Stake, therefore, energy-efficient. Herein the consensus is achieved by a BFT algorithm which is linearl
36#
發(fā)表于 2025-3-27 19:54:22 | 只看該作者
A Six-Point Based Approach for Enhanced Broadcasting Using Selective Forwarding Mechanism in Mobilemits during broadcasting. The proposed technique considerably improved by selecting only an ideal selection of transmission nodes, so reducing redundant broadcasts and ensuring that the data received is equivalent to the information originated.
37#
發(fā)表于 2025-3-28 00:15:44 | 只看該作者
38#
發(fā)表于 2025-3-28 02:29:56 | 只看該作者
Towards the Prominent Use of Internet of Things (IoT) in Universities, knowledge students possess in terms of IoT technologies and whether IoT systems have an influence on students’ learning. The study targeted students in the IT fields due to the fact that they are more exposed to the IoT infrastructure. The findings reveal that IT students have IoT knowledge which n
39#
發(fā)表于 2025-3-28 09:58:58 | 只看該作者
40#
發(fā)表于 2025-3-28 14:17:02 | 只看該作者
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