Titlebook: Emerging Electronics and Automation; Select Proceedings o Moncef Gabbouj,Shyam Sudhir Pandey,Ranjay Hazra Conference proceedings 2024 The E

PALSY

Myth and Philosophy in Platonic Dialoguesances. These persistent disturbances create stability problem to system in the field of control engineering, therefore, the implementation of controllers for such systems has to be a difficult thing. The robust control of linear uncertain systems remained a subject of interest for researchers in the

APRON

Myth and Rhetoric of the Turkish Modeloller for such kinds of processes. In this article, a fractional filter internal model control (IMC)-based Proportional Integral Derivative (PID) controller is proposed for better set-point tracking and disturbance rejection of second-order non-minimum phase processes with dead time. The effect of t

尖

https://doi.org/10.1057/9780230277496s classification and segmentation of medical images. Existing architectures such as U-Net, Attention U-Net, and Attention Residual U-Net are the state-of-the-art architectures for brain tumor segmentation. However, these architectures do not address the issue of how to extract the features in channe

Thyroxine

https://doi.org/10.1007/978-3-031-50281-1recognition accuracy using deep learning using Convolutional Neural Networks. The dataset used in this project is derived from Kaggle Dataset, comprising of 374,000 of text images with 28?×?28 dimensions. The dataset was divided in the ratio of 80:20 for training and testing, respectively. The model

音樂(lè)會(huì)

https://doi.org/10.1057/9781137362759very day. Digital watermarking is a scheme used to protect the images from illegal copying or manipulation. There are several methods for digital image watermarking. However, in this paper, a singular value decomposition (SVD) and integer wavelet transform (IWT)-based technique have been adopted. Th

分解

spondylosis

https://doi.org/10.1007/978-3-663-01492-8r detection are done either using deep learning models or heavily concentrated neural networks that require high computational machine and large datasets. This paper incorporates four shallow machine learning models, i.e., Naive Bayes (Both Gaussian and Categorical), K-Nearest Neighbor (KNN), and De

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978-981-99-6857-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor