Performance Evaluation of Artificial Neural Network Methods Based on Block Machine Learning Classification by Raya Hamdy, Mohammed Younis

“…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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Sequence and taxonomic feature evaluation facilitated the discovery of alcohol oxidases by Yilei Han, Xuwei Ding, Junjian Tan, Yajuan Sun, Yunjiang Duan, Zheng Liu, Gaowei Zheng, Diannan Lu

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

“…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

“…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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Multi-Scale Feature Similarity and Object Detection for Small Printing Defects Detection by Haojie Lou, Yuanlin Zheng, Wenqian Chen, Haiwen Liu

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Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks by Osheen Sharma, Greta Gudoityte, Rezan Minozada, Olli P. Kallioniemi, Riku Turkki, Lassi Paavolainen, Brinton Seashore-Ludlow

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CANini: In-Depth Traffic Analysis for Design and Robustness Evaluation of DTree-Based IDS in Automotive Networking Systems by Nicasio Canino, Pierpaolo Dini, Stefano Mazzetti, Daniele Rossi, Sergio Saponara

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SE-CapsNet: Automated evaluation of plant disease severity based on feature extraction through Squeeze and Excitation (SE) networks and Capsule networks by Shradha Verma, Anuradha Chug, Ravinder P. Singh, Amit P. Singh, Dinesh Singh

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Evaluating Features and Variations in Deepfake Videos Using the CoAtNet Model by Eman Alattas, John Clark, Arwa Al-Aama, Salma Kammoun Jarraya

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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

“…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

“…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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A framework for online social networking features by Mohsen Shafiei Nikabadi, Fatemeh Maleki

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Evaluation of initial geostress field of underground powerhouse in the complex alteration area of western Sichuan based on back-propagation neural network method by Hong Zheng, Shiqi Cao, Quan Jiang, Shaojun Li, Dingping Xu, Zhiwei Li

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Evaluating ORB and SIFT With Neural Network as Alternatives to CNN for Traffic Classification in SDN Environments by Hicham Yzzogh, Hafssa Benaboud

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A database to initiate methodological advances in the evaluation of transitivity assumption in network meta-analysis: qualitative features and limitations of the tracenma R package by Loukia M. Spineli, Andrés Mauricio García-Sierra, Juan Jose Yepes-Nuñez

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SHARP-Net: A Refined Pyramid Network for Deficiency Segmentation in Culverts and Sewer Pipes by Rasha Alshawi, Md Meftahul Ferdaus, Md Tamjidul Hoque, Kendall Niles, Ken Pathak, Steve Sloan

“…SHARP-Net combines multiscale feature fusion, depthwise separable convolutions, and fine-tuned Haar-like features to enhance performance while reducing computational complexity. …”
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Embedded feature selection using dual-network architecture by Abderrahim Abbassi, Arved Dörpinghaus, Niklas Römgens, Tanja Grießmann, Raimund Rolfes

“…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

“…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

“…To address this issue, we propose an Adaptive Feature Interactive Enhancement Network (AFIENet). …”
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Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

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