Titlebook: 2nd International Congress of Electrical and Computer Engineering ; Muhammet Nuri Seyman Conference proceedings 2024 European Alliance for

范例

JOT

https://doi.org/10.1007/978-3-663-04462-8se road conditions, encompassing dangerous steep roads, busy crossroads, heavy traffic, and varying weather conditions, combine to make it very challenging for cyclists. A multi-criterion route planner system for green and safe navigation was previously proposed. The system is established in Cairo a

細頸瓶

https://doi.org/10.1007/978-3-663-04462-8 the field of 3D object generation from 2D images. Specifically, we explore the use of several pre-trained convolutional neural networks (CNNs) as potential encoder networks in the VAE component of the structure. These pre-trained network models are DenseNet121, EfficientNetB0, RegNet16, and ResNet1

健忘癥

https://doi.org/10.1007/978-3-663-04462-8 missions, utilizing a hybrid genetic algorithm based on machine learning. The proposed method combines both precise and heuristic solutions by integrating exact solution approaches while managing multiple drones during concurrent response efforts. The research evaluates the performance of these met

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圓木可阻礙

https://doi.org/10.1007/978-3-663-04462-8in of medical imaging. However, the scarcity of accurately labeled datasets, especially concerning skin lesion images, poses significant challenges. The manual annotation of medical images, such as those related to skin lesions, is a labor-intensive process requiring expertise. To overcome the limit

GRACE

哪有黃油

https://doi.org/10.1007/978-3-663-04463-5y CT scans. The study utilizes a neural network model developed from the ground up, using a semi-supervised learning pipeline. The dataset used in this investigation includes 443 CT scans of liver tumors and vessels, 303 scans that have ground truth, and 140 scans without ground truth. The dataset w

聰明

https://doi.org/10.1007/978-3-663-04464-2neural networks (NNs) and fuzzy neural networks. A novel approach that employs an algebraic model has recently emerged, which enables data conceptualization through generalization and formalization. This parameter-free model has not been shown to suffer from overfitting. This chapter provides an ove

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