Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…The approach integrates multiple ranking and projection techniques for features, utilizing deep learning to detect early signs of liver disease. …”
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Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning by Ali Altalbe

“…This work implements and validates the FFS-IDS using real-time car hacking data sets and achieves better performance than individual decision tree classifiers and popular ensemble learning methods such as Random Forest, LightGBM, AdaBoost, and ExtraTree algorithms. The results demonstrate that FFS-IDS can detect Denial of Service (DoS), Gear spoofing, and RPM spoofing attacks with up to 99% accuracy and Fuzzy attacks with up to 97.5% accuracy using benchmark datasets. …”
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A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

“…Nonetheless, in spam detection, there are a large number of features to attend as they play an essential role in detection efficiency. …”
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A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

“…Finally, a heuristic search strategy-based algorithm is designed to select features for epileptic EEG signals. …”
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An IoT intrusion detection framework based on feature selection and large language models fine-tuning by Huan Ma, Wan Zhang, Dalong Zhang, Baozhan Chen

“…This algorithm utilizes the CMA-ES algorithm for feature search while also taking into account the mutual information and collinearity among features, thereby more effectively reducing redundancy features. …”
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Spatial-Temporal Semantic Feature Interaction Network for Semantic Change Detection in Remote Sensing Images by Yuhang Zhang, Wuxia Zhang, Songtao Ding, Siyuan Wu, Xiaoqiang Lu

“…The “from-to” information of the acquired image has more profound practical significance than Binary Change Detection (BCD). However, most deep learning-based SCD algorithms do not fully exploit the spatial-temporal information of multilevel features, leading to challenges in extracting LCLU features in complex scenes. …”
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Sea Clutter Suppression Method Based on Correlation Features by Zhen Li, Huafeng He, Liyuan Wang, Tao Zhou, Yizhe Sun, Yaomin He

“…Then, it uses these speckle components to derive the feature subspace of the sea clutter and applies this subspace in an orthogonal projection suppression algorithm, thereby achieving effective suppression of the sea clutter. …”
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Local Sub-Block Contrast and Spatial–Spectral Gradient Feature Fusion for Hyperspectral Anomaly Detection by Dong Zhao, Xingchen Xu, Mingtao You, Pattathal V. Arun, Zhe Zhao, Jiahong Ren, Li Wu, Huixin Zhou

“…However, they often overlook the spatial–spectral gradient information inherent in hyperspectral images, which can lead to decreased detection accuracy. To address this limitation, we propose a novel hyperspectral anomaly detection algorithm that incorporates both local sub-block contrast and spatial–spectral gradient features. …”
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Fault Detection System of Photovoltaic Based on Artificial Neural Network by Ali Salman Zamzeer, Mansour S. Farhan, Haider TH. ALRikabi

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Integrated artificial immune system for intrusion detection by Yue-bing CHEN, Chao FENG, Quan ZHANG, Chao-jing TANG

“…According to the practical requirements of intrusion detection,an integrated artificial immune system (IAIS) was proposed.The system combined dendritic cell algorithm(DCA)and negative selection algorithm(NSA).DCA was used to detect behavioral features.NSA was used to detect structural features.IAIS was validated on KDD 99 dataset.Comparisons to other approaches were made.The experimental results show that the detection performance of IAIS is comparable to classic classification algorithm.IAIS does not rely on labeled data to train detectors.It combines behavioral features and structural features to detect intrusions in real-time mode.…”
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Enhanced Fall Detection and Prediction Using Heterogeneous Hidden Markov Models in Indoor Environment by Oumaima Guendoul, Hamd Ait Abdelali, Youness Tabii, Rachid Oulad Haj Thami, Omar Bourja

“…This study employs an Heterogenous Hidden Markov Model (HHMM) that utilizes 3D vision-based body articulation data to propose an innovative method for fall detection and prediction. To ensure the precision and reliability of our model, we preprocessed the data to eliminate noise and extract pertinent features. …”
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Insulator discharge severity assessment algorithm based on RDIDSNet by Cheng Chi, Li Keyu, Yanhui Meng, Yang Yang, JiNing Zhao, Shaotong Pei, Haosen Sun

“…Abstract For the insulator discharge severity assessment at the line inspection site using edge-end computing equipment and UV cameras, this paper proposes an improved assessment algorithm based on the YOLOv8 algorithm. Firstly, LDConv is introduced to replace the convolution of the backbone network part of the network feature extraction, which effectively realizes the enhancement of the feature extraction ability of the algorithm in the case of model lightweighting; and then ACMix attention mechanism is introduced, which realizes better focusing of the model on the target with a very small performance loss; and finally, Shape-IoU is introduced to replace the loss function of the CIoU, which effectively improve the detection accuracy of the algorithm. …”
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AI-Based Ransomware Detection: A Comprehensive Review by Jannatul Ferdous, Rafiqul Islam, Arash Mahboubi, Md Zahidul Islam

“…This study contributes significantly to the development of a systematic evaluation framework that evaluates each component of the AI-based detection model framework using specific criteria and methodologies and analyzes how various AI algorithms respond to different ransomware attacks, thereby providing insights for more effective and robust detection methods. …”
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Image Matching Algorithm for Transmission Towers Based on CLAHE and Improved RANSAC by Ruihua Chen, Pan Yao, Shuo Wang, Chuanlong Lyu, Yuge Xu

“…To address the lack of robustness against illumination and blurring variations in aerial images of transmission towers, an improved image matching algorithm for aerial images is proposed. The proposed algorithm consists of two main components: an enhanced AKAZE algorithm and an improved three-stage feature matching strategy, which are used for feature point detection and feature matching, respectively. …”
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The Detection Optimization of Low-Quality Fake Face Images: Feature Enhancement and Noise Suppression Strategies by Ge Wang, Yue Han, Fangqian Xu, Yuteng Gao, Wenjie Sang

“…To address these limitations, this paper proposes a novel algorithm, YOLOv9-ARC, which is designed to enhance the accuracy of detecting low-quality fake facial images. …”
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Green Apple Detection Method Based on Multidimensional Feature Extraction Network Model and Transformer Module by Wei Ji, Kelong Zhai, Bo Xu, Jiawen Wu

“…To enhance the fast and accurate detection of pollution-free green apples for food safety, this paper uses the DETR network as a framework to propose a new method for pollution-free green apple detection based on a multidimensional feature extraction network and Transformer module. …”
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Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. …”
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An Intrusion Detection Model Based on Feature Selection and Improved One-Dimensional Convolutional Neural Network by Qingfeng Li, Bo Li, Linzhi Wen

“…Traditional machine learning techniques to intrusion detection rely on expert experience to choose features, and deep learning approaches have a low detection efficiency. …”
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A Multi-Index Fusion Adaptive Cavitation Feature Extraction for Hydraulic Turbine Cavitation Detection by Yi Wang, Feng Li, Mengge Lv, Tianzhen Wang, Xiaohang Wang

“…A multi-index fusion adaptive cavitation feature extraction and cavitation detection method is proposed to solve the above problems. …”
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Edge-Guided Feature Pyramid Networks: An Edge-Guided Model for Enhanced Small Target Detection by Zimeng Liang, Hua Shen

“…We conducted comparative experiments on multiple datasets using the proposed algorithm and existing advanced methods. The results show improvements in the IoU, nIoU, and F1 metrics, while also showcasing the lightweight nature of EG-FPNs, confirming that they are more suitable for drone detection in resource-constrained infrared scenarios.…”
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