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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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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Spectroscopic detection of cotton Verticillium wilt by spectral feature selection and machine learning methods by Weinan Li, Weinan Li, Weinan Li, Lisen Liu, Jianing Li, Weiguang Yang, Weiguang Yang, Yang Guo, Yang Guo, Longyu Huang, Longyu Huang, Zhaoen Yang, Jun Peng, Jun Peng, Xiuliang Jin, Xiuliang Jin, Yubin Lan, Yubin Lan

“…Initial analysis identified critical spectral reflectance bands, wavelet coefficients, and SIs that exhibited dynamic responses as the disease progressed.ResultsModel validation demonstrated that the incidence detection models at the leaf scale achieved a peak classification accuracy of 85.83%, which is about 10% higher than traditional methods without feature selection. …”
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Ventricular Fibrillation Prediction and Detection: A Comprehensive Review of Modern Techniques by Monica Fira, Hariton-Nicolae Costin, Liviu Goraș

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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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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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Class-weighted Dempster–Shafer in dual-level fusion for multimodal fake real estate listings detection by Maifuza Mohd Amin, Nor Samsiah Sani, Mohammad Faidzul Nasrudin

“…This underscores the potential of integrating multimodal analysis with sophisticated fusion techniques to enhance the detection of fake property listings, ultimately improving consumer protection and operational efficiency in online real estate platforms.…”
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Smartphone sensor-based depression detection in campus environments: a proof-of-concept study with small-sample behavioral analysis by Yichen Bai, Yueze Liu, Yang Zhang, Amr Tolba

Subjects: “…depression detection…”
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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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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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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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Breast Lesion Detection Using Weakly Dependent Customized Features and Machine Learning Models with Explainable Artificial Intelligence by Simona Moldovanu, Dan Munteanu, Keka C. Biswas, Luminita Moraru

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Predicting Invasiveness in Lepidic Pattern Adenocarcinoma of Lung: Analysis of Visual Semantic and Radiomic Features by Sean F. Johnson, Seyed Mohammad Hossein Tabatabaei, Grace Hyun J. Kim, Bianca E. Villegas, Matthew Brown, Scott Genshaft, Robert D. Suh, Igor Barjaktarevic, William Dean Wallace, Fereidoun Abtin

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An active learning driven deep spatio-textural acoustic feature ensemble assisted learning environment for violence detection in surveillance videos by Duba Sriveni, Dr.Loganathan R

“…In this paper, a novel and robust deep spatio-textural acoustic feature ensemble-assisted learning environment is proposed for violence detection in surveillance videos (DestaVNet). …”
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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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Signal Processing and Feature Extraction in Markerless Telerehabilitation by Silvana G. Dellepiane, Federica Ferraro, Camilla Baffigo, Marina Simonini

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A review of deep learning in blink detection by Jianbin Xiong, Weikun Dai, Qi Wang, Xiangjun Dong, Baoyu Ye, Jianxiang Yang

“…Compared with traditional methods, the blink detection method based on deep learning offers superior feature learning ability and higher detection accuracy. …”
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A Network Analysis Approach to Detect and Differentiate Usher Syndrome Types Using miRNA Expression Profiles: A Pilot Study by Rama Krishna Thelagathoti, Wesley A. Tom, Chao Jiang, Dinesh S. Chandel, Gary Krzyzanowski, Appolinaire Olou, Rohan M. Fernando

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Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer by Chaoyang Li, Zhipeng He, Kai Lu, Chaoyang Fang

“…Bird species detection is critical for applications such as the analysis of bird population dynamics and species diversity. …”
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