Comparison of Clustering Algorithms: Fuzzy C-Means, K-Means, and DBSCAN for House Classification Based on Specifications and Price by Dhendy Mardiansyah Putra, Ferian Fauzi Abdulloh

“…This study aims to compare the performance of three clustering algorithms, namely Fuzzy C-Means, K-Means, and DBSCAN, in grouping houses based on their specifications and prices. …”
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A method for synthetic speech detection using local phase quantization by Jia XU, Zhihua JIAN, Honghui JIN, Man YANG

“…Due to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward using the information in spectral domain of the synthetic speech spectrogram.The method employed the local phase quantization (LPQ) algorithm to describe frequency domain information in the speech spectrogram.Firstly, the spectrogram was divided into several sub-blocks, and then the LPQ was performed on each sub-block.After the histogram statistical analysis, the LPQ feature vector was obtained and used as the input feature of the random forest classifier to realize the synthetic speech detection.The experimental results demonstrate that the proposed method further reduces tandem detection cost function (t-DCF) and has better generalization ability.…”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Unsupervised Fabric Defect Detection Based on Under-Complete Dictionary Reconstruction by LIU Jianxin, PAN Ruru, ZHOU Jian

“…The proposed algorithm achieved an average correct detection rate of 83.29% on the AITEX dataset, demonstrating its effectiveness.…”
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An intrusion detection mechanism for IPv6-based wireless sensor networks by Min Wei, Chunmeng Rong, Erxiong Liang, Yuan Zhuang

“…This mechanism trains an intrusion detection algorithm using a feature data set to create a normal profile. …”
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A New Local Optimal Spline Wavelet for Image Edge Detection by Dujuan Zhou, Zizhao Yuan, Zhanchuan Cai, Defu Zhu, Xiaojing Shen

“…We propose a new LOSW-based edge detection algorithm (LOSW-ED), which introduces a structural uncertainty–aware modulus maxima (SUAMM) to detect highly uncertain edge samples, ensuring robustness in complex and noisy environments. …”
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SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…This study proposes an enhanced SR-DETR algorithm aimed at improving the detection of individuals who have fallen overboard. …”
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FEXGBIDS: Federated XGBoost-Based Intrusion Detection System for In-Vehicle Network by Jie Li, Yuanyuan Song, Ming-Gang Zheng, Shuo Zhang, Han Liang

“…Additionally, we employ BLS aggregate signatures to achieve efficient and verifiable parameter aggregation, and leverage the DDSketch distributed quantile estimation algorithm to optimize the feature bucketing process. …”
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CGTS: graph transformer-based anomaly detection in controller area networks by Xue Zhou, Guihe Qin, Yanhua Liang, Jiaru Song, Wanning Liu, Qingxin Liu

“…While existing anomaly detection strategies offer some benefits, they often face challenges such as limited feature extraction and data imbalance, which reduce their effectiveness. …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. …”
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Towards a Scalable and Adaptive Learning Approach for Network Intrusion Detection by Alebachew Chiche, Million Meshesha

“…Interestingly, significant knowledge rich learning for intrusion detection differs as a fundamental feature of intrusion detection and prevention techniques. …”
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Foreign Object Detection on Insulators Based on Improved YOLO v3 by Huankun ZHANG, Junyi LI, Bin ZHANG

“…The experiment shows that the proposed algorithm has a detection precision rate reaching up to 94.54%. …”
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Comparative Model Efficiency Analysis Based on Dissimilar Algorithms for Image Learning and Correction as a Means of Fault-Finding by Joe Benganga, Tshepo Kukuni, Ben Kotze, Lepekola Lenkoe

“…As a result of the opportunities that artificial intelligence presents to different sectors by optimally performing tasks with less error compared to humans or traditional models, the use of AI in artefact detection is being investigated. This research paper thus presents a comparative model efficiency analysis based on dissimilar algorithms, namely CNN, VGG16, Inception_V3, and ResNet_50. …”
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Hybrid attention transformer integrated YOLOV8 for fruit ripeness detection by Jianyin Tang, Zhenglin Yu, ChangShun Shao

“…In addition, during the feature fusion stage, the Hybrid Attention Transformer (HAT) module is integrated into TopDownLayer2 to enhance the capture of long-term dependencies and the recovery of detailed information in the input data. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…This work presents a new method for sleeper crack identification based on cascade convolutional neural network (CNN) to address the problem of low efficiency and poor accuracy in the traditional detection method of sleeper crack identification. The proposed algorithm mainly includes improved You Only Look Once version 3 (YOLOv3) and the crack recognition network, where the crack recognition network includes two modules, the crack encoder-decoder network (CEDNet) and the crack residual refinement network (CRRNet). …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Abstract The ever-growing number of complex cyber attacks requires the need for high-level intrusion detection systems (IDS). While the available research deals with traditional, hybrid, and ensemble methods for network data analysis, serious challenges are still being met in terms of producing robust and highly accurate detection systems. …”
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Lightweight Detection of Train Underframe Bolts Based on SFCA-YOLOv8s by Zixiao Li, Jinjin Li, Chuanlong Zhang, Huajun Dong

“…By combining the C2f module with ScConv lightweight convolution and replacing the Bottleneck structure with the Faster_Block structure, the SFC2f module is designed for feature extraction to improve detection accuracy and speed. …”
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Detection and Geolocation of Peat Fires Using Thermal Infrared Cameras on Drones by Temitope Sam-Odusina, Petrisly Perkasa, Carl Chalmers, Paul Fergus, Steven N. Longmore, Serge A. Wich

“…Finally, a geolocation algorithm is presented to identify the GNSS location of these fires once they are detected in an image to aid fire-fighting responses. …”
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Early Yield Prediction of Oilseed Rape Using UAV-Based Hyperspectral Imaging Combined with Machine Learning Algorithms by Hongyan Zhu, Chengzhi Lin, Zhihao Dong, Jun-Li Xu, Yong He

“…Meanwhile, optimized feature selection algorithms identified effective wavelengths (EWs) and vegetation indices (VIs) for yield estimation. …”
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GES: A New Building Damage Data Augmentation and Detection Method Based on Extremely Imbalanced Data and Unique Spatial Distribution of Satellite Images by Xiaopeng Sha, Zhoupeng Guo, Xinqi Sang, Shuyu Wang, Yuliang Zhao

“…The experimental research on the proposed algorithm is conducted using the mainstream object detection models. …”
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