Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…Notably, we performed feature engineering to optimize the input data; specifically, we derived 20 key features from transformation functions applied to the SERS spectra. …”
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Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection by Onur Polat, Ali Ayid Ahmad, Saadin Oyucu, Enes Algul, Ferdi Dogan, Ahmet Aksoz

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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

“…The results show that LR performed best in terms of accuracy, with an F1 score of 76.77. Using Random Forest feature ranking and SHAP analysis revealed that many comments on Albanian social media exhibit unique characteristics, resulting in a large feature set. …”
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Improving Object Detection for Time-Lapse Imagery Using Temporal Features in Wildlife Monitoring by Marcus Jenkins, Kirsty A. Franklin, Malcolm A. C. Nicoll, Nik C. Cole, Kevin Ruhomaun, Vikash Tatayah, Michal Mackiewicz

“…Traditional methods, which require extensive fieldwork, are increasingly being supplemented by time-lapse camera-trap imagery combined with an automatic analysis of the image data. The latter usually involves some object detector aimed at detecting relevant targets (commonly animals) in each image, followed by some postprocessing to gather activity and population data. …”
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Spatial features of CO2 for occupancy detection in a naturally ventilated school building by Qirui Huang, Marc Syndicus, Jérôme Frisch, Christoph van Treeck

“…In this study, we present two novel features for occupancy detection based on the spatial distribution of the CO2 concentration. …”
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A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…First, image standardization, including size normalization and background removal, is applied to produce standard images; then, the modified dynamic histogram equalization is implemented to enhance the low-contrast standard brain images, and skull removal based on outlier detection is presented. Furthermore, hybrid features, including gray-level co-occurrence matrix, pyramid histogram of the oriented gradient, modified completed local binary pattern, and intensity-based features are extracted together from the enhanced images, and their dimensions are reduced by principal component analysis. …”
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Reinforcement Learning With Deep Features: A Dynamic Approach for Intrusion Detection in IoT Networks by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…The extracted feature sets were concatenated within a feature fusion layer that enabled efficient dimensionality reduction via principal component analysis. …”
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Managing Feature Compatibility in Kubernetes: Vendor Comparison and Analysis by Eddy Truyen, Nane Kratzke, Dimitri Van Landuyt, Bert Lagaisse, Wouter Joosen

“…Our analysis focuses on the potential of the end-to-end testing suite of Kubernetes to detect support for a desired feature in any Kubernetes vendor and the possibility of reconfiguring the studied vendors with missing features in a uniform manner. …”
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Evaluation of Key Remote Sensing Features for Bushfire Analysis by Ziyi Yang, Husam Al-Najjar, Ghassan Beydoun, Bahareh Kalantar, Mohsen Zand, Naonori Ueda

“…This study evaluates remote sensing features to resolve problems associated with feature redundancy, low efficiency, and insufficient input feature analysis in bushfire detection. …”
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StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images by Evren Ekingen, Ferhat Yildirim, Ozgur Bayar, Erhan Akbal, Ilknur Sercek, Abdul Hafeez-Baig, Sengul Dogan, Turker Tuncer

“…In the DFE pipeline, StrokeNeXt extracts features from fixed‑size patches, iterative neighborhood component analysis (INCA) selects the top features, and a t algorithm-based k-nearest neighbors (tkNN) classifier has been utilized for classification. …”
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Methodological features of the analysis of the fractal dimension of the heart rate by M. O. Bykova, V. A. Balandin

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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

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COVID-19 detection from chest CT images using optimized deep features and ensemble classification by Muhammad Minoar Hossain, Md. Abul Ala Walid, S.M. Saklain Galib, Mir Mohammad Azad, Wahidur Rahman, A.S.M. Shafi, Mohammad Motiur Rahman

“…Moreover, pertinent features are identified from the feature vector by using several feature optimization methods namely Recursive feature elimination (RFE), Principal component analysis (PCA), and Linear discriminant analysis (LDA), and among them, we have observed PCA as the best preference. …”
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Chloroplast genome features and phylogenetic analysis of Artemisia parviflora by LI Zhifang, CHEN Liling, LUO Shujie, LIU Tianmeng*

“…To explore the structural features of Artemisia parviflora chloroplast genome and its systematic position, high-throughput sequencing technology were employed for genome sequencing and bioinformatics tools for analyzing. …”
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TSFANet: Trans-Mamba Hybrid Network with Semantic Feature Alignment for Remote Sensing Salient Object Detection by Jiayuan Li, Zhen Wang, Nan Xu, Chuanlei Zhang

“…Although existing methods improve detection accuracy by optimizing feature extraction and attention mechanisms, they still face limitations when dealing with the inherent challenges of ORSI. …”
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Signal Processing and Feature Extraction in Markerless Telerehabilitation by Silvana G. Dellepiane, Federica Ferraro, Camilla Baffigo, Marina Simonini

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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…This paper emphasizes the main issues in fraud detection and suggests a novel feature selection method called FID-SOM (feature selection for imbalanced data using SOM). …”
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Interpretable graph methods for determining nanoparticles ordering in electron microscopy image by M.Y. Kurbakov, V.V. Sulimova, O.S. Seredin, A.V. Kopylov

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CLASSIFYING ANDROID MALWARE CATEGORIES BASED ON DYNAMIC FEATURES: AN INTEGRATION OF FEATURE REDUCTION AND SELECTION TECHNIQUES by abdullah alsraratee, Ahmed Al-Azawei

“…This study utilizes machine learning techniques namely, K-Nearest Neighbor, Random Forest and Decision Tree to classify Android malware based on dynamic analysis. As feature selection and reduction techniques, Mutual Information and Principle Component Analysis are used. …”
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A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

“…Current methods for epilepsy EEG signal recognition typically extract and represent features from multiple dimensions, such as temporal, spectral, and time–frequency analysis. …”
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