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    Evaluating Packaging Design Relative Feature Importance Using an Artificial Neural Network (ANN) by Juan Gu, Euihark Lee

    Published 2025-03-01
    “…The findings of this study demonstrate the effectiveness of artificial neural network (ANN)-based approaches in evaluating the relative importance of packaging design features. …”
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    An Empirical Evaluation of Supervised Learning Methods for Network Malware Identification Based on Feature Selection by C. Manzano, C. Meneses, P. Leger, H. Fukuda

    Published 2022-01-01
    “…In the literature, it is reported that this good performance can depend on a reduced set of network features. This study presents an empirical evaluation of two statistical methods of reduction and selection of features in an Android network traffic dataset using six supervised algorithms: Naïve Bayes, support vector machine, multilayer perceptron neural network, decision tree, random forest, and K-nearest neighbors. …”
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    Performance Evaluation of Artificial Neural Network Methods Based on Block Machine Learning Classification by Raya Hamdy, Mohammed Younis

    Published 2023-12-01
    “…Thirty cat photos from the Oxford-IIIT Pet dataset were used for evaluation. Five different Artificial Neural Network (ANN) models, including LM, BGFGS, RP, SCG, and GDX, were trained and assessed for both pixel-based and block-based methods. …”
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    Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction by Amun Jarzembski, Siddharth Nair, Wyatt Hodges, Matthew Jordan, Anthony McDonald, Logan Antiporda, Greg W. Pickrell, Timothy Walsh, Fabio Semperlotti, Jason Neely, Luke Yates

    Published 2025-07-01
    “…Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. …”
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    A Multicriteria Decision-Making Approach for Urban Water Features: Ecological Landscape Architecture Evaluation by Reyhaneh Hashemi Sigari, Thomas Panagopoulos

    Published 2024-10-01
    “…To this end, a multicriteria decision-making method, an analytic network process, was proposed to quantitatively evaluate the ecological characteristics of water features. …”
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    Embedded feature selection using dual-network architecture by Abderrahim Abbassi, Arved Dörpinghaus, Niklas Römgens, Tanja Grießmann, Raimund Rolfes

    Published 2025-09-01
    “…However, existing methods often face challenges due to the complexity of feature interdependencies, uncertainty regarding the exact number of relevant features, and the need for hyperparameter optimization, which increases methodological complexity.This research proposes a novel dual-network architecture for feature selection that addresses these issues. …”
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    Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

    Published 2025-03-01
    “…Furthermore, while feature selection benefits simpler algorithms (such as RF), normalization is more useful for complex algorithms like ANNs and deep neural networks (DNNs), and algorithms such as Naive Bayes are unsuitable for IDS modeling. …”
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    Adaptive feature interaction enhancement network for text classification by Rui Su, Shangbing Gao, Kefan Zhao, Junqiang Zhang

    Published 2025-04-01
    “…To address this issue, we propose an Adaptive Feature Interactive Enhancement Network (AFIENet). …”
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    GeoAT: Geometry-Aware Attention Feature Matching Network by Yan Li, Yingdan Wu, Yang Ming, Yong Zhang, Zhesheng Cheng

    Published 2025-01-01
    “…This method leverages low-resolution image features to obtain global geometric constraint information between images and uses an affine transformation matrix to guide the subsequent attention computation on high-resolution features, achieving efficient and accurate matching in a coarse-to-fine manner. …”
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