Deep Learning Innovations for Underwater Waste Detection: An In-Depth Analysis by Jaskaran Singh Walia, Kavietha Haridass, L. K. Pavithra

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RF-RFE-SMOTE: A DoS And DDoS Attack Detection Framework by Nora Rashid Najam, Razan Abdulhammed Abduljawad

“…The framework comprises three main modules: feature selection method using Random Forest—Recursive Feature Elimination (RF-RFE), handling the Imbalanced class distributions using Synthetic Minority Oversampling Technique (SMOTE), and classification. …”
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DSCnet: detection of drug and alcohol addiction mechanisms based on multi-angle feature learning from the hybrid representation of EEG by Jing Wu, Nan Zhang, Qilei Ye, Xiaorui Zheng, Minmin Shao, Xian Chen, Hui Huang

“…Electroencephalography (EEG) is commonly used to analyze addiction mechanisms, but traditional feature extraction methods such as time-frequency analysis, Principal Component Analysis (PCA), and Independent Component Analysis (ICA) fail to capture complex relationships between variables.MethodsThis paper proposes DSCnet, a novel neural network model for addiction detection. …”
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Detecting forest and linear woody feature change between 1954 and 2019 in Southeastern Canadian agroecosystems for regional biodiversity assessment by Darren Pouliot, Niloofar Alavi, Mao Mao, Jon Pasher, Jason Duffe

“…Effectively mapping and detecting changes in forests and linear woody features (LWFs) is crucial for assessing their impact on biodiversity and ecosystem services. …”
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Study of the metabolome features of patients with COVID-19 by Y. V. Russkikh, N. N. Sushentseva, O. S. Popov, S. V. Apalko, A. Yu. Anisenkova, S. V. Mosenko, A. M. Sarana, S. G. Shcherbak

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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…This study presents a novel Computer-Aided Diagnosis of Haematologic Disorders Detection Based on Spatial Feature Learning Networks with Hybrid Model (CADHDD-SFLNHM) approach using Blood Cell Images. …”
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AFF_CGE: Combined Attention-Aware Feature Fusion and Communication Graph Embedding Learning for Detecting Encrypted Malicious Traffic by Junhao Liu, Guolin Shao, Hong Rao, Xiangjun Li, Xuan Huang

“…While encryption enhances data security, it also presents significant challenges for network traffic analysis, especially in detecting malicious activities. …”
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BaAM-YOLO: a balanced feature fusion and attention mechanism based vehicle detection network in aerial images by Xunxun Zhang, Xu Zhu

“…Vehicle detection in aerial imagery is of paramount importance for various intelligent transportation applications, including vehicle tracking, traffic control, and traffic behavior analysis. …”
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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…We proposed a hybrid approach uses automated feature engineering via correlation-based feature selection (CFS) and principal component analysis (PCA)-based dimensionality reduction to reduce feature matrix size before a series of dense layers are used for classification. …”
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Artificial intelligence with feature fusion empowered enhanced brain stroke detection and classification for disabled persons using biomedical images by Mohammed Alsieni, Khaled H. Alyoubi

“…Artificial intelligence technologies, primarily deep learning (DL), have been widely employed in medical imaging, utilizing automated detection methods. This paper presents an Enhanced Brain Stroke Detection and Classification using Artificial Intelligence with Feature Fusion Technologies (EBSDC-AIFFT) model. …”
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QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals by Veysel Yusuf Cambay, Irem Tasci, Gulay Tasci, Rena Hajiyeva, Sengul Dogan, Turker Tuncer

“…An XFE model has been presented to detect stress automatically. The presented XFE model has four main phases, and these are (i) channel transformer and quadruple transition pattern (QuadTPat)-based feature generation, (ii) feature selection deploying cumulative weighted neighborhood component analysis (CWNCA), (iii) explainable results creation with DLob and (iv) classification with t algorithm-based k-nearest neighbors (tkNN) classifier. …”
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Enhancing cerebral infarct classification by automatically extracting relevant fMRI features by Vitaly I. Dobromyslin, Wenjin Zhou, for the Alzheimer’s Disease Neuroimaging Initiative

“…The best-performing combination of biomarkers and classifiers achieved a cross-validation ROC score of 0.791, closely matching the accuracy of diffusion-weighted imaging methods used in acute stroke detection. Our proposed auto-ML fMRI infarct-detection technique demonstrated robustness across diverse imaging sites and scanner types, highlighting the potential of automated feature extraction to significantly enhance non-invasive infarct detection.…”
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Detecting Malicious .NET Executables Using Extracted Methods Names by Hamdan Thabit, Rami Ahmad, Ahmad Abdullah, Abedallah Zaid Abualkishik, Ali A. Alwan

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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…Classification is widely and largely used in data analysis, and pattern recognition. The data analysis aims to discover similarities between them and group them based on similarity into multiple classes. …”
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Semantic Features-Based Discourse Analysis Using Deceptive and Real Text Reviews by Husam M. Alawadh, Amerah Alabrah, Talha Meraj, Hafiz Tayyab Rauf

“…The final results indicate that semantically aware features inspire more confidence to detect deception in text.…”
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Plastid genomic features and phylogenetic placement in Rosa (Rosaceae) through comparative analysis by Hui Jiang, Shuilian He, Jun He, Yunjuan Zuo, Wenling Guan, Yan Zhao, Xuejiao Li, Jing Meng

“…Abundant SSRs (73–87) and long repeat sequences (36–52) were detected in Rosa plastomes, and most of these repeats could be found within the IGS region. …”
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A Full-Scale Shadow Detection Network Based on Multiple Attention Mechanisms for Remote-Sensing Images by Lei Zhang, Qing Zhang, Yu Wu, Yanfeng Zhang, Shan Xiang, Donghai Xie, Zeyu Wang

“…Shadows degrade image quality and complicate interpretation, underscoring the importance of accurate shadow detection for many image analysis tasks. However, due to the complex backgrounds and variable shadow characteristics of remote sensing images (RSIs), existing methods often struggle with accurately detecting shadows of various scales and misclassifying dark, non-shaded areas as shadows. …”
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Towards Parkinson’s Disease Detection Through Analysis of Everyday Handwriting by Jeferson David Gallo-Aristizabal, Daniel Escobar-Grisales, Cristian David Ríos-Urrego, Jesús Francisco Vargas-Bonilla, Adolfo M. García, Juan Rafael Orozco-Arroyave

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Detection of bulbar amyotrophic lateral sclerosis based on speech analysis by A. D. Gvozdovich, Y. N. Rushkevich, M. I. Vashkevich

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Analysis for Detecting Banana Leaf Disease Using the CNN Method by Nita Helmawati, Ema Utami

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