Profiling Astroturfers on Facebook: A Complete Framework for Labeling, Feature Extraction, and Classification by Jonathan Schler, Elisheva Bonchek-Dokow

“…The ability to automatically identify astroturfers thus constitutes a first step in eradicating this threat. We present a complete framework for handling a dataset of profiles, from data collection and efficient labeling, through feature extraction, and finally, to the identification of astroturfers lurking in the dataset. …”
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Association Rule-Based Feature Mining for Automated Fault Diagnosis of Rolling Bearing by Yuan Li, Jinjiang Wang, Lixiang Duan, Tangbo Bai, Xuduo Wang, Yulong Zhang, Guoliang Qin

“…Comparing with conventional fault diagnosis methods taking a forward approach (e.g., feature extraction, feature selection, and fusion, and then fault diagnosis), this paper presents a new association rule mining method which provides an inverse approach unearthing the underlying relation between labeled defects and extracted features for bearing fault analysis. …”
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Conversion disorder in children and adolescents: clinical features and comorbidity with depressive and anxiety disorders by B Pehlivantürk, F Unal

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Exploring unsupervised feature extraction algorithms: tackling high dimensionality in small datasets by Hongqi Niu, Gabrielle B. McCallum, Anne B. Chang, Khalid Khan, Sami Azam

“…These datasets often contain high-dimensional features, yet present significant challenges of dimensionality, wherein the sparsity of data in high-dimensional spaces makes it difficult to extract meaningful information and less accurate predictive models are produced. …”
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Remote Sensing Surveillance Using Multilevel Feature Fusion and Deep Neural Network by Laiba Zahoor, Haifa F. Alhasson, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz Alhammadi, Ahmad Jalal, Hui Liu

“…Our system presents a reliable drone-based human action system through the integration of state-of-the-art methods for multilevel feature extraction and object detection. …”
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Guided Particle Swarm Optimization for Feature Selection: Application to Cancer Genome Data by Simone A. Ludwig

“…This paper presents a feature selection method based on Particle Swarm Optimization (PSO). …”
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Ultrasound tomography enhancement by signal feature extraction with modular machine learning method. by Bartłomiej Baran, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, Tomasz Rymarczyk

“…Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography. …”
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Feature Screening via Mutual Information Learning Based on Nonparametric Density Estimation by Shengbin Zhou, Tao Wang, Yejin Huang

“…With the advent of the era of big data, feature selection in high- or ultra-high-dimensional data is increasingly important in statistics and machine learning fields. …”
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UFM: Unified feature matching pre-training with multi-modal image assistants. by Yide Di, Yun Liao, Hao Zhou, Kaijun Zhu, Qing Duan, Junhui Liu, Mingyu Lu

“…We present Multimodal Image Assistant (MIA) transformers, finely tunable structures adept at handling diverse feature matching problems. …”
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Integrating Correlation-Based Feature Selection and Clustering for Improved Cardiovascular Disease Diagnosis by Agnieszka Wosiak, Danuta Zakrzewska

“…Experiment results showed the advantage of the presented approach compared to other feature selection methods and without using clustering to support statistical inference.…”
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Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

“…Despite these advances, a key problem lies in defining the configuration criteria of the adaptive algorithm. This study presents an adaptive variant of PSO that relies on fitness landscape analysis, particularly via ruggedness factor estimation. …”
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A feature-based intelligent deduplication compression system with extreme resemblance detection by Xiaotong Wu, Jiaquan Gao, Genlin Ji, Taotao Wu, Yuan Tian, Najla Al-Nabhan

“…In this paper, we study the problem of utilising the duplicate and resemblance detection techniques to further compress data. We first present a framework of FIDCS-ERD, a feature-based intelligent deduplication compression system with extreme resemblance detection. …”
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Efficient feature selection for histopathological image classification with improved multi-objective WOA by Ravi Sharma, Kapil Sharma, Manju Bala

“…Furthermore, the majority of current approaches have approached feature selection as a single objective issue. This research presents an enhanced multi-objective whale optimisation algorithm-based feature selection technique as a solution. …”
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Automated facial feature evaluation system to prevent stress of head fixed mice. by Anna Nasr, Gianna Rettinger, Huibert D Mansvelder, Robert N S Sachdev, Matthew E Larkum

“…Conventional stress evaluation methods, such as blood corticosterone analysis, are labor-intensive and conducted post hoc, and In situ approaches require experienced personnel and constant vigilance during experiments. In this study, we present MouseCare, an automated software solution for immediate stress detection by real-time facial feature video analysis in head-fixed mice. …”
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A modular and adaptable approach for automated morphological feature extraction in meibography images by Itziar Fernández, Andrea Novo-Diez, María J. González-García

“…Abstract This study presents a modular and adaptable approach for the automated extraction of morphological features from meibography images, focusing on Meibomian gland (MG) analysis. …”
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Unsupervised feature selection based on generalized regression model with linear discriminant constraints by Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai

“…To tackle these challenges, we present a novel unsupervised feature selection method that leverages the generalized regression model with linear discriminant constraints to learn discriminant and effective features from the data. …”
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Liver segmentation network based on detail enhancement and multi-scale feature fusion by Lu Tinglan, Qin Jun, Qin Guihe, Shi Weili, Zhang Wentao

“…Furthermore, to enable the model to better learn liver features at different scales, a Multi-Scale Feature Fusion module (MSFF) is added to the skip connections in the model. …”
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Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

“…A case study with interpretable machine learning is also presented in the paper.…”
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Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

“…Conclusions Microbiome data transformations can significantly influence feature selection but have a limited effect on classification accuracy. …”
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Eye movements and attention in visual feature search with graded target-distractor-similarity by Carolin Wienrich, Uta Heße, Gisela Müller-Plath

“…We conducted a visual feature search experiment in which we varied the target-distractor-similarity in four steps, the number of items (4, 6, and 8), and the presence of the target. …”
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