Recent Advancement in Small Traffic Sign Detection: Approaches and Dataset by R. Suresha, N. Manohar, G. Ajay Kumar, M. Rohit Singh

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Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition by Erhan Bergil, Murat Yıldız

“…It is aimed to detect different epileptic stage. In this study, performances of Wavelet Transform and Empirical Mode Decomposition methods which are used commonly to extract feature in epilepsy studies have been compared. …”
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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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Thermographic Data Processing and Feature Extraction Approaches for Machine Learning-Based Defect Detection by Alexey Moskovchenko, Michal Svantner

“…Data preparation and feature extraction are crucial factors affecting ML model results, especially in thermographic data analysis. …”
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Tree-Based Algorithms and Incremental Feature Optimization for Fault Detection and Diagnosis in Photovoltaic Systems by Khaled Chahine

“…A comprehensive dataset analysis is conducted to improve the dataset quality and uncover intricate relationships between features and the target variable. …”
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Urban object detection algorithm based on feature enhancement and progressive dynamic aggregation strategy by Luxuan Bian, Zijun Gao, Jue Wang, Bo Li

“…These challenges can result in loss of feature information and missed object detection. In light of this, this article introduces a novel dual-gated feature mechanism and adaptive fusion strategy. …”
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Enhanced Anomaly Detection in IoT Networks Using Deep Autoencoders with Feature Selection Techniques by Hamza Rhachi, Younes Balboul, Anas Bouayad

“…More specifically, we propose and implement a model that uses DAE (deep autoencoder) to detect and classify the network data, with an ANOVA F-Test for the feature selection. …”
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Adaptive Robust Low-Beam Feature Point Detection Algorithm Based on Convex Hull by Qiqi Shen, Jie Wu

“…The existing algorithms for detecting low-beam feature points are neither universally applicable nor effective. …”
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A novel feature extraction method based on dynamic handwriting for Parkinson's disease detection. by Huimin Lu, Guolian Qi, Dalong Wu, Chenglin Lin, Songzhe Ma, Yingqi Shi, Han Xue

“…Although many features have been proposed in previous researches, the insight analysis of the combination of handwriting's kinematic, pressure, and angle dynamic features is lacking. …”
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A quantitative benchmark of neural network feature selection methods for detecting nonlinear signals by Antoine Passemiers, Pietro Folco, Daniele Raimondi, Giovanni Birolo, Yves Moreau, Piero Fariselli

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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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Damage Detection in Machining Tools Using Acoustic Emission, Signal Processing, and Feature Extraction by Lucas Pires Bernardes, Pedro Oliveira Conceição Júnior, Fabio Romano Lofrano Dotto, Alessandro Roger Rodrigues, Marcio Marques Silva

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A Novel Copula-Based Multi-Feature CFAR Framework for Radar Target Detection by Juan Li, Yunlong Dong, Ningbo Liu, Yong Huang, Xingyu Jiang, Jinping Sun

“…Multi-feature radar target detection enhances the discrimination between targets and clutter, thereby improving detection accuracy. …”
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Multi-Branch Network with Multi-Feature Enhancement for Improving the Generalization of Facial Forgery Detection by Siyu Meng, Quange Tan, Qianli Zhou, Rong Wang

“…To further enhance the facial forgery detection ability, spatial pyramid pooling is introduced into the classifier to augment the fused features. …”
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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 Hierarchical Feature Fusion and Dynamic Collaboration Framework for Robust Small Target Detection by Xu Yan, Junliang Du, Xuan Li, Xiaoye Wang, Xiaoxuan Sun, Pochun Li, Hongye Zheng

“…Small target detection is an important research direction in computer vision, widely applied in scenarios such as drone monitoring, remote sensing image analysis, and autonomous driving. …”
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Novel transfer learning based acoustic feature engineering for scene fake audio detection by Ahmad Sami Al-Shamayleh, Hafsa Riasat, Ala Saleh Alluhaidan, Ali Raza, Sahar A. El-Rahman, Diaa Salama AbdElminaam

“…Abstract Audio forensics plays a major role in the investigation and analysis of audio recordings for legal and security purposes. …”
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Dynamically Tunable Multidimensional Feature Focusing and Diffusion Networks for Water Surface Debris Detection by Chong Zhang, Jie Yue, Jianglong Fu

“…Furthermore, a Focal-Diffuse Feature Pyramid Network (FD-FPN) was introduced to accurately capture and integrate key feature information through focused feature fusion techniques while utilizing cross-scale diffusion analysis to efficiently transfer and enhance feature information across different scales. …”
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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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Copy-Move Forgery Detection Technique Using Graph Convolutional Networks Feature Extraction by Varun Shinde, Vineet Dhanawat, Ahmad Almogren, Anjanava Biswas, Muhammad Bilal, Rizwan Ali Naqvi, Ateeq Ur Rehman

“…By pulling data from this image, GCN is able to obtain content rich features that are very powerful at detecting CMF regions. …”
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