Lightweight Deepfake Detection Based on Multi-Feature Fusion by Siddiqui Muhammad Yasir, Hyun Kim

“…In order to reduce the computational burden usually associated with DL models, our method integrates machine learning classifiers in combination with keyframing approaches and texture analysis. Moreover, the features extracted with a histogram of oriented gradients (HOG), local binary pattern (LBP), and KAZE bands were integrated to evaluate using random forest, extreme gradient boosting, extra trees, and support vector classifier algorithms. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…However, both types of boosting algorithms struggle with the analysis of complex feature sets, the enhancement of weak learners, and the handling of larger datasets. …”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…Thus, this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets: NSL-KDD, UNSW-NB15, and CSE–CIC–IDS2018, and various AI algorithms. …”
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MAHGA: Multi-Aspect Heterogeneous Graph Analysis for Harmful Speech Detection on Social Networks by Ryo Yoshida, Soh Yoshida, Mitsuji Muneyasu

Subjects: “…Harmful speech detection…”
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LD-Det: Lightweight Ship Target Detection Method in SAR Images via Dual Domain Feature Fusion by Hang Yu, Bingzong Liu, Lei Wang, Teng Li

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Detecting Important Features and Predicting Yield from Defects Detected by SEM in Semiconductor Production by Umberto Amato, Anestis Antoniadis, Italia De Feis, Anastasiia Doinychko, Irène Gijbels, Antonino La Magna, Daniele Pagano, Francesco Piccinini, Easter Selvan Suviseshamuthu, Carlo Severgnini, Andres Torres, Patrizia Vasquez

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A Survey of Machine Learning Techniques Leveraging Brightness Indicators for Image Analysis in Biomedical Applications by Hajer Ghodhbani, Suvendi Rimer, Khmaies Ouahada, Adel M. Alimi

“…This paper presents a comprehensive survey of machine-learning techniques that leverage brightness indicators for image analysis within biomedical applications. By examining commonalities and challenges in brightness-based analysis, this survey provides insights into machine learning (ML) methods that enhance interpretability, noise reduction, and feature detection in the biomedical field. …”
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Smart Grid Intrusion Detection for IEC 60870-5-104 With Feature Optimization, Privacy Protection, and Honeypot-Firewall Integration by Pedamallu Sai Mrudula, Rayappa David Amar Raj, Archana Pallakonda, Yanamala Rama Muni Reddy, K. Krishna Prakasha, V. Anandkumar

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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

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Detection of network intelligence features with the decision tree model by N. P. Sharaev, S. N. Petrov

“…The study was carried out to develop software module for detecting the features of network intelligence by machine learning methods.M e t h o d s . …”
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Explainable handcrafted features for mitotic event detection and classification by Panason Manorost, Thomas Deckers, Veerle Bloemen, Jean Marie Aerts

“…The applied machine learning approach not only allows high processing performance but also explains how selected features contribute to mitotic event detection. The mean accuracy of the classifiers is 85.12% and precision and recall for the publicly available phase contrast dataset are 88.01% and 92.70% respectively. …”
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Detection method of LDoS attacks based on combination of ANN ＆ KPCA by Zhijun WU, Liang LIU, Meng YUE

“…Low-rate denial-of-service (LDoS) attack is a new type of attack mode for TCP protocol.Characteristics of low average rate and strong concealment make it difficult for detection by traditional DoS detecting methods.According to characteristics of LDoS attacks,a new LDoS queue future was proposed from the router queue,the kernel principal component analysis (KPCA) method was combined with neural network,and a new method was present to detect LDoS attacks.The method reduced the dimensionality of queue feature via KPCA algorithm and made the reduced dimension data as the inputs of neural network.For the good sell-learning ability,BP neural network could generate a great LDoS attack classifier and this classifier was used to detect the attack.Experiment results show that the proposed approach has the characteristics of effectiveness and low algorithm complexity,which helps the design of high performance router.…”
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Speech Analysis as a Tool for Detection and Monitoring of Medical Conditions: A review by Magdalena IGRAS-CYBULSKA, Daria HEMMERLING, Mariusz ZIÓŁKO, Wojciech DATKA, Ewa STOGOWSKA, Michał KUCHARSKI, Rafał RZEPKA, Bartosz ZIÓŁKO

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Multi-scale aware dual path network for face detection in resource-constrained edge computing environment by Qi QI, Yingxin MA, Jingyu WANG, Haifeng SUN, Jianxin LIAO

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An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

“…Primarily, the EALAI-CFDNBD model utilized the linear scaling normalization (LSN) model to ensure that the input features were appropriately scaled for subsequent analysis. …”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…While the chaotic indices, including Lyapunov Exponent (LE), Fractal Dimension (FD), Kolmogorov-Sinai Entropy (KSE), and Correlation Dimension (CD), are employed for nonlinear analysis, the Gray-Level Co-occurrence Matrix (GLCM) method utilized for extracting the texture features. …”
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Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis by Lior Molcho, Neta B. Maimon, Talya Zeimer, Ofir Chibotero, Sarit Rabinowicz, Vered Armoni, Noa Bar On, Nathan Intrator, Ady Sasson

“…Abstract Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. …”
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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

Subjects: “…brain tumor detection…”
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Feature Extraction from Regenerated EEG – A Better Approach for ICA Based Eye Blink Artifact Detection by Maliha Rashida, Mohammad Ashfak Habib

“…Feature extraction from the decomposed ICs is a prime step for blink detection. …”
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Analysis of Cardiac Arrhythmias Based on ResNet-ICBAM-2DCNN Dual-Channel Feature Fusion by Chuanjiang Wang, Junhao Ma, Guohui Wei, Xiujuan Sun

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