Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection by Rong Pang, Yan Yang, Aiguo Huang, Yan Liu, Peng Zhang, Guangwu Tang

“…Therefore, this paper proposes an MFF based on regional feature Aggregation (MFF-A), which reduces the missed detection rate of bridge defect detection and improves the positioning accuracy of the target area. …”
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Feature Selection Using Pearson Correlation for Ultra-Wideband Ranging Classification by Gita Indah Hapsari, Rendy Munadi, Bayu Erfianto, Indrarini Dyah Irawati

“…These findings highlight the effectiveness of Pearson correlation-based feature selection in improving UWB-based indoor positioning systems. …”
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Innovating Cybersecurity in Tanzanian Academia: A Mobile Tool for Combatting Social Engineering Threats by Lucas Hosea Mjema, Bonny Said Mgawe, Mussa Ally Dida

“…Our findings demonstrate that a mobile-based, user-centric approach can significantly bolster cybersecurity awareness and incident response in academic environments. …”
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MFEAM: Multi-View Feature Enhanced Attention Model for Image Captioning by Yang Cui, Juan Zhang

“…Transformer has become the dominant language model in image captioning. Existing Transformer-based models seldom highlight important features from multiple views in the use of self-attention. …”
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Deep Sparse Autoencoder for Feature Extraction and Diagnosis of Locomotive Adhesion Status by Changfan Zhang, Xiang Cheng, Jianhua Liu, Jing He, Guangwei Liu

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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

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Feature Representation Using Deep Autoencoder for Lung Nodule Image Classification by Keming Mao, Renjie Tang, Xinqi Wang, Weiyi Zhang, Haoxiang Wu

“…The visual vocabulary is constructed based on the local features and bag of visual words (BOVW) is used to describe the global feature representation of lung nodule image. …”
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Improved Quaternion Discriminant Analysis for Feature Extraction and Classification of Hyperspectral Image by Xinpeng Wang, Bingo Wing-Kuen Ling, Long Yu, Shaopeng Liu, Jiandong Zhao, Weichao Kuang

“…As a result, the effect of feature extraction is not ideal. Besides, in the case of small samples, using quaternion discriminant analysis (QDA) based on Cos-sin decomposition, the matrix obtained by the first orthogonal trigonometric decomposition is not a diagonal matrix, that makes the projection axis not optimal. …”
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Adaptive deep feature representation learning for cross-subject EEG decoding by Shuang Liang, Linzhe Li, Wei Zu, Wei Feng, Wenlong Hang

“…Specifically, we first minimize the distribution discrepancy between the source and target domains by employing maximum mean discrepancy (MMD) regularization, which aids in learning the shared feature representations. We then utilize the instance-based discriminative feature learning (IDFL) regularization to make the learned feature representations more discriminative. …”
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Hyperbolic geometry enhanced feature filtering network for industrial anomaly detection by Yanjun Feng, Jun Liu, Yonggang Gai

“…Additionally, challenges such as addressing pre-trained feature redundancy and bias in the pre-training process persist. …”
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A novel federated learning approach for IoT botnet intrusion detection using SHAP-based knowledge distillation by Md. Alamgir Hossain, Sadman Saif, Md. Saiful Islam

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An ensemble machine learning approach for classification tasks using feature generation by Wenjuan Feng, Jin Gou, Zongwen Fan, Xiang Chen

“…In this case, two new features are generated from the combination of probabilities based on these base classifiers. …”
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Optimizing Feature Selection for IOT Intrusion Detection Using RFE and PSO by zahraa mehssen agheeb Alhamdawee

“…The best results were obtained using RF and kNN classifiers that were trained with features selected by RFE. kNN benefits from the smaller feature space since it focuses on distance measures, which are more successful with a refined set of features. …”
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Investigating feature extraction by SIFT methods for prostate cancer early detection by Shadan Mohammed Jihad, Ali A. Alsaud, Firas H. Almukhtar, Shahab Kareem, Raghad Zuhair Yousif

“…The adopted methodology was based on the comparative analysis and benchmarking of the performance of feature extraction based on SIFT against traditional image processing techniques with a generic representation on a number of metrics: sensitivity, specificity, and overall diagnostic accuracy. …”
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Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN by Ming Zeng, Min Wang, Fuqiang Xie, Zhiwei Ji

“…These methods excel by extracting both topological and feature information from DTIs networks, thereby achieving superior DTIs prediction performance. …”
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Enhancing Multi–Class Prediction of Skin Lesions with Feature Importance Assessment by Paulauskaite-Taraseviciene Agne, Sutiene Kristina, Dimsa Nojus, Valiukeviciene Skaidra

“…For this purpose, we addressed both binary and five-class classification tasks using a small dataset, with skin lesions prevalent in Lithuania. The model was trained using a rich set of 662 features, encompassing both conventional image features and graph-based ones, which were obtained from the superpixel graph generated using Delaunay triangulation. …”
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Discriminative Features Extraction for Plant Disease Classification Using Deep CNN by Hira Farman, usman Amjad

“…To improve the model performance further techniques like data augmentation, contrast enhancement, noise reduction techniques were used. The training results of the proposed CNN had a training loss of 0.0808 and a validation loss of 0.3330.The training as well as the validation accuracy achieved were 97.41% as well as 90.34% respectively. …”
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JDroid: Android malware detection using hybrid opcode feature vector by Recep Sinan Arslan

“…In this study, we propose a tool called JDroid that treats opcodes (Dalvik Opcode and Java ByteCode) as features based on static analysis. The proposed tool aims to detect malicious applications with a unique ensemble model in a stacked generalised structure that uses different opcode sequences as a hybrid, and where each feature is first trained separately and then used by an ensemble decision. …”
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Development of a nomogram-based model incorporating radiomic features from follow-up longitudinal lung CT images to distinguish invasive adenocarcinoma from benign lesions: a retro... by Zhengming Wang, Fei Wang, Yan Yang, Weijie Fan, Li Wen, Dong Zhang

“…Logistic regression was used to build models based on clinicoradiological (CR), T0, T1, and delta radiomic features and compute signatures. …”
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Features of road safety project implementation until 2024 in Omsk region by E. A. Safronov, K. E. Safronov

“…Research is carried out at the Organization and Traffic Safety Department and is introduced into the educational process and implemented at the Federal Training Center for advanced training of workers involved in the training of drivers, created in SibADI.Discussion and conclusion. …”
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