Research and Application of SURF and Gray Difference in Detection of Small Modulus Plastic Gear Defect by Yang Ya, Tao Hongyan, Yu Chengbo

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Non-Negative Matrix Factorization and Latent Semantic Analysis for Hybrid Feature Selection: A Proposed Machine Learning System for the Detection of Malicious Executable Files by Moemedi Lefoane, Ibrahim Ghafir, Sohag Kabir, Irfan-Ullah Awan, Khalil El Hindi, Anand Mahendran

Subjects: “…Feature selection…”
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Enhancing voice spoofing detection in noisy environments using frequency feature masking augmentation by Soyul Han, Jaejin Seo, Sunmook Choi, Taein Kang, Sanghyeok Chung, Seungeun Lee, Seoyoung Park, Seungsang Oh, Il-Youp Kwak

“…Our exploratory data analysis revealed that for a given speech sample, noisy signals tend to occur within similar frequency bands. …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

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Brain tumor detection across diverse MR images: An automated triple-module approach integrating reduced fused deep features and machine learning by Yugal Pande, Jyotismita Chaki

“…The first module utilizes pre-trained deep learning models (DenseNet121 and ResNet101) to extract informative features. The second module employs Principal Component Analysis (PCA) for dimensionality reduction. …”
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Enhanced detection of malaria infected red blood cells through phase driven classification by Charlotte Kyeremah, Aditya S. Paul, Daniel Haehn, Manoj T. Duraisingh, Chandra S. Yelleswarapu

“…The parasitemia detection rate improved from 48% (feature-specific method) to 61% (phase-based features method) on the same sample set, demonstrating enhanced detection accuracy. …”
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Detection of Potentially Anomalous Cosmic Particle Tracks Acquired with CMOS Sensors: Validation of Rough k–Means Clustering with PCA Feature Extraction by Hachaj Tomasz, Piekarczyk Marcin, Wąs Jarosław

“…We apply a principal components analysis-based feature extraction method and rough k-means clustering for outlier detection. …”
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Back Propagation Neural Network model for analysis of hyperspectral images to predict apple firmness by Shuiping Li, Yueyue Chen, Xiaobo Zhang, Junbo Wang, Xuanxiang Gao, Yunhong Jiang, Zhaojun Ban, Cunkun Chen

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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

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DDA-MSLD: A Multi-Feature Speech Lie Detection Algorithm Based on a Dual-Stream Deep Architecture by Pengfei Guo, Shucheng Huang, Mingxing Li

“…This combination enables the network to more comprehensively capture the context of speech signals and focus on the parts that are more critical for lie detection. It can perform in-depth sequence pattern analysis on manually extracted static prosodic features and nonlinear dynamic features, obtaining high-order dynamic features related to lies. …”
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Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomograp... by Diletta Pennati, Leonardo Bocchi

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Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

Subjects: “…Intrusion detection system…”
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A hybrid deep learning framework for early detection of Mpox using image data by Sajal Chakroborty

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Research on Surface Defects Classification for PET Preform by Fusing Multi-Scale Features by Chunmei Duan, Taochuan Zhang, Lei Han, Huilin Tan

“…Multi-scale features fusion combines features from different scales to produce more accurate and robust feature representations, which improve the accuracy, stability and adaptability of PET preform detection model. …”
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Autism Spectrum disorder Detection in Toddlers and Adults Using Deep Learning by Abbas Sidra, Ojo Stephen, Krichen Moez, Alamro Meznah A., Mihoub Alaeddine, Vilcekova Lucia

“…Data analysis is carried out to detect anomalies and outliers, and a label encoding technique is utilized to convert the categorical data into numerical values. …”
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Acoustic-based machine learning approaches for depression detection in Chinese university students by Yange Wei, Yange Wei, Shisen Qin, Fengyi Liu, Rongxun Liu, Yunze Zhou, Yuanle Chen, Xingliang Xiong, Wei Zheng, Guangjun Ji, Yong Meng, Fei Wang, Fei Wang, Ruiling Zhang

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Effectiveness of Feature Extraction by PCA-Based Detection and Naive Bayes Classifier for Glaucoma Images by J. Shiny Christobel, D. Vimala, J. Joshan Athanesious, S. Christopher Ezhil Singh, Sivaraj Murugan

“…This paper presents the methodology to detect the glaucoma using principal component analysis. …”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…First, simulation experiments and model analysis determine the keyframe and flight trajectory. …”
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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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Automated multi-model framework for malaria detection using deep learning and feature fusion by Osama R. Shahin, Hamoud H. Alshammari, Raed N. Alabdali, Ahmed M. Salaheldin, Neven Saleh

“…The framework employs a transfer learning approach that incorporates ResNet 50, VGG16, and DenseNet-201 for feature extraction. This is followed by feature fusion and dimensionality reduction via principal component analysis. …”
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