A Novel Feature Extraction Method for Nonintrusive Appliance Load Monitoring by Khaled Chahine, Khalil El Khamlichi Drissi

“…This system captures the signals from the aggregate consumption, extracts the features from these signals and classifies the extracted features in order to identify the switched-on appliances. …”
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A New Method for Iris Segmentation and Feature Extraction in Spatial Domain by Dujan Taha, Shamil Ibraheem

“…Finally, Matlab R2010a (Ver. 7.10.0) was used to implement the algorithms presented in this paper because it facilitates handling images, arrays, and filters.…”
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Bearing fault diagnosis method based on dual-channel feature fusion by ZHANG Xiaoning, ZHU Huilong, XIN Liang, YANG Muchen, WANG Hao

“…To solve this limitation, this paper presents a rolling bearing fault diagnosis method based on dual-channel feature fusion. …”
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Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy by Tu‐Lan Vu‐Han, Vikram Sunkara, Rodrigo Bermudez‐Schettino, Jakob Schwechten, Robin Runge, Carsten Perka, Tobias Winkler, Sebastian Pokutta, Claudia Weiß, Matthias Pumberger

“…Conclusion The introduction of disease‐modifying SMA therapies, followed by the implementation of SMA in newborn screenings, has presented physicians with never‐seen patients. We used feature engineering tools to overcome one of the main challenges when using data‐driven approaches in rare disease data sets. …”
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Feature Generation with Genetic Algorithms for Imagined Speech Electroencephalogram Signal Classification by Edgar Lara-Arellano, Andras Takacs, Saul Tovar-Arriaga, Juvenal Rodríguez-Reséndiz

“…This algorithm can efficiently explore ample feature space and identify the most relevant features for the task. …”
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Audio Feature Space Analysis for Emotion Recognition from Spoken Sentences by Lukasz SMIETANKA, Tomasz MAKA

“…An analysis of low-level feature space for emotion recognition from the speech is presented. …”
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Influential nodes identification for complex networks based on multi-feature fusion by Shaobao Li, Yiran Quan, Xiaoyuan Luo, Juan Wang

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An Indoor Scene Classification Method for Service Robot Based on CNN Feature by Shaopeng Liu, Guohui Tian

“…To solve this problem, an indoor scene classification method is proposed in this paper, which utilizes CNN feature of scene images to generate scene category features to classify scenes by a novel feature matching algorithm. …”
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A Deep Learning Approach for Spatiotemporal Feature Classification of Infrasound Signals by Xiaofeng Tan, Xihai Li, Hongru Li, Xiaoniu Zeng, Shengjie Luo, Tianyou Liu

“…Infrasound signal classification remains a critical challenge in geophysical monitoring systems, where classification performance is fundamentally constrained by feature extraction efficacy. Existing two-dimensional feature extraction methods suffer from inadequate representation of spatiotemporal signal dynamics, leading to performance degradation in long-distance detection scenarios. …”
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Band Selection Algorithm Based on Multi-Feature and Affinity Propagation Clustering by Junbin Zhuang, Wenying Chen, Xunan Huang, Yunyi Yan

“…However, due to the characteristics of hyperspectral remote sensing images—such as high redundancy, strong correlation, and large data volumes—the classification and recognition of these images present significant challenges. In this paper, we propose a band selection method (GE-AP) based on multi-feature extraction and the Affine Propagation Clustering (AP) algorithm for dimensionality reduction of hyperspectral images, aiming to improve classification accuracy and processing efficiency. …”
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Evaluating Sparse Feature Selection Methods: A Theoretical and Empirical Perspective by Monica Fira, Liviu Goras, Hariton-Nicolae Costin

“…The mathematical foundations of feature selection methods inspired by compressed detection are presented, highlighting how the principles of sparse signal recovery can be applied to identify the most relevant features. …”
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PVLF: point-voxel local feature fusion for 3D detection by Haowei Zhao, Zhuolei Xiao

“…However, existing algorithms still face significant challenges in detecting tiny objects such as cyclists and pedestrians. This paper presents a novel feature fusion method named Point Voxel Local Feature Fusion (PVLF), which deeply integrates point cloud and voxel information. …”
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Adversarial detection based on feature invariant in license plate recognition systems by ZHU Xiaoyu, TANG Peng, ZHANG Haochen, QIU Weidong, HUANG Zheng

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LPFFNet: Lightweight Prior Feature Fusion Network for SAR Ship Detection by Xiaozhen Ren, Peiyuan Zhou, Xiaqiong Fan, Chengguo Feng, Peng Li

“…To address the issue, a lightweight prior feature fusion network (LPFFNet) is proposed to better improve the performance of SAR ship detection. …”
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An Improved DGA Feature Clustering-Based Method for Transformer Fault Diagnosis by Yujie Zhang, Jian Feng, Shanyuan Wang

“…Fault diagnosis of transformers based on a clustering algorithm primarily utilizes the proportional data of dissolved gases as features, which have not considered abundant gas ratio features, and those clustering methods are prone to invalid clustering. …”
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The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping by Gregory D. Vetaw, Suren Jayasuriya

“…We then modify the BFT to present a difference of trigonometric functions to mitigate speckle scatterers and other random noise sources found in the imagery. …”
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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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Feature Integration Strategies for Neural Speaker Diarization in Conversational Telephone Speech by Juan Ignacio Alvarez-Trejos, Alicia Lozano-Diez, Daniel Ramos

“…This paper addresses the challenge of optimizing end-to-end neural diarization systems for conversational telephone speech, focusing on diverse acoustic features beyond traditional Mel-filterbanks. We present a methodological framework for integrating and analyzing different feature types as input to the well-known End-to-End Neural Diarization with Encoder Decoder Attractors (EEND-EDA) model, focusing on Emphasized Channel Attention, Propagation and Aggregation in Time Delay Neural Network (ECAPA-TDNN) embeddings and Geneva Minimalistic Acoustic Parameter Sets (GeMAPS). …”
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Visual Odometry through Appearance- and Feature-Based Method with Omnidirectional Images by David Valiente García, Lorenzo Fernández Rojo, Arturo Gil Aparicio, Luis Payá Castelló, Oscar Reinoso García

“…Particularly, we exploited the versatility of the information gathered by omnidirectional images to perform both an appearance-based and a feature-based method to obtain visual odometry results. …”
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Feature of Ocular-Ischemic Syndrome in Patients with Cardiovascular Pathology. Literature Review by M. A. Frolov, N. A. Sakhovskaya, A. M. Frolov, A. D. Pryamikov

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