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

Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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

Subjects: Get full text

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

Get full text

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

Get full text

A Multi-Path Feature Extraction and Transformer Feature Enhancement DEM Super-Resolution Reconstruction Network by Mingqiang Guo, Feng Xiong, Ying Huang, Zhizheng Zhang, Jiaming Zhang

“…The network structure has three parts: feature extraction, image reconstruction, and feature enhancement. …”
Get full text

DOA Estimation by Feature Extraction Based on Parallel Deep Neural Networks and MRMR Feature Selection Algorithm by Ashwaq Neaman Hassan Al-Tameemi, Mahmood Mohassel Feghhi, Behzad Mozaffari Tazehkand

“…In parallel, the proposed model extracts spatial and temporal features using a convolution neural network (CNN) and long short-term memory (LSTM). …”
Get full text

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

Get full text

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. …”
Get full text

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. …”
Get full text

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). …”
Get full text

Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

Get full text

GeoAT: Geometry-Aware Attention Feature Matching Network by Yan Li, Yingdan Wu, Yang Ming, Yong Zhang, Zhesheng Cheng

“…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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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

Get full text

Hybrid feature learning framework for the classification of encrypted network traffic by S. Ramraj, G. Usha

“…Previous research has shown that deep learning methods are effective in the feature learning process, so this study uses a simple feed-forward Deep Neural Network (DNN) to improve the performance of the SVM algorithm. …”
Get full text

SLFCNet: an ultra-lightweight and efficient strawberry feature classification network by Wenchao Xu, Yangxu Wang, Jiahao Yang

“…Methods In this study, we have developed a lightweight model capable of real-time detection and classification of strawberry fruit, named the Strawberry Lightweight Feature Classify Network (SLFCNet). This innovative system incorporates a lightweight encoder and a self-designed feature extraction module called the Combined Convolutional Concatenation and Sequential Convolutional (C3SC). …”
Get full text