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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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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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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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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Efficient Method for Robust Backdoor Detection and Removal in Feature Space Using Clean Data by Donik Vrsnak, Marko Subasic, Sven Loncaric

“…This method can detect and reconstruct the feature representation of the possible triggers used in attacking the neural network. …”
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A stacked ensemble approach to detect cyber attacks based on feature selection techniques by Wahida Ferdose Urmi, Mohammed Nasir Uddin, Md Ashraf Uddin, Md. Alamin Talukder, Md. Rahat Hasan, Souvik Paul, Moumita Chanda, John Ayoade, Ansam Khraisat, Rakib Hossen, Faisal Imran

“…The exponential growth of data and increased reliance on interconnected systems have heightened the need for robust network security. Cyber-Attack Detection Systems (CADS) are essential for identifying and mitigating threats through network traffic analysis. …”
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Microblog hot topic detection method based on meaningful string clustering by Min HE, Li-hong WANG, Pan DU, Jin ZHANG, Xue-qi CHENG

“…Aiming at the properties of sparse feature, content fragmentation for microblog data, a hot topic detection method was proposed based on meaningful string clustering. …”
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Microblog hot topic detection method based on meaningful string clustering by Min HE, Li-hong WANG, Pan DU, Jin ZHANG, Xue-qi CHENG

“…Aiming at the properties of sparse feature, content fragmentation for microblog data, a hot topic detection method was proposed based on meaningful string clustering. …”
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AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…To address these issues, we propose an Attention-Free Hybrid Network (AFHNet) for underwater optical image analysis. AFHNet integrates an attention-free mechanism, global feature enhancement, and a convolution-free Transformer-based dual-encoder to effectively fuse RGB and depth features while preserving essential information. …”
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Machine Learning-Based Acoustic Analysis of Stingless Bee (<i>Heterotrigona itama</i>) Alarm Signals During Intruder Events by Ashan Milinda Bandara Ratnayake, Hartini Mohd Yasin, Abdul Ghani Naim, Rahayu Sukmaria Sukri, Norhayati Ahmad, Nurul Hazlina Zaini, Soon Boon Yu, Mohammad Amiruddin Ruslan, Pg Emeroylariffion Abas

“…Among them, Linear Discriminant Analysis (LDA) demonstrated the best performance in improving class separability. …”
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A Weak Signal Detection Method Based on HFER Features in Sea Clutter Background by Yan Yan, Yongxian Song, Hongyan Xing, Zhengdong Qi

“…We conducted a comparative analysis using the BCD, RAA, TIE, SVM, and multi-feature fusion detection methods. …”
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Different Biometrical Features for Detecting Human Intrusion Using Artificial Intelligence: Literature Review by Ansam Younis

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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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