Tuberculosis Detection using Gray Level Co-Occurrence Matrix (GLCM) and K-Nearest Neighbor (K-NN) Algorithms by Fuad Anwar, Mohtar Yunianto*, Rahmanisya Fani Aisha Putri

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LMAD-YOLO: A vehicle image detection algorithm for drone aerial photography based on multi-scale feature fusion. by Xue Xing, Fahui Luo, Le Wan, Kang Lu, Yuqi Peng, Xiujuan Tian

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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

“…However, existing speech lie detection algorithms still have certain limitations. …”
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Optimal deep learning based vehicle detection and classification using chaotic equilibrium optimization algorithm in remote sensing imagery by Youseef Alotaibi, Krishnaraj Nagappan, Tamilvizhi Thanarajan, Surendran Rajendran

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IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT by Sefri Imanuel Fallo, Lidia Paskalia Nipu

“…This research is primarily dedicated to providing a comprehensive exposition of the methodology applied in the deployment of a cartographic-based machine learning algorithm designed for the precise identification of areas susceptible to landslides within the geographical confines of the Takari District.This research delves into the application of mapping-based machine learning algorithms in the domain of non-structural disaster mitigation, with a specific emphasis on the detection of landslide susceptibility within the Takari District. …”
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Retracted: Detection and Analysis of Man-Machine Interactive Software Vulnerabilities Based on Ultrasonic Data Acquisition and Signal Processing Algorithms by Advances in Multimedia

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A Three-Dimensional FDTD(2,4) Subgridding Algorithm for the Airborne Ground-Penetrating Radar Detection of Landslide Models by Lifeng Mao, Xuben Wang, Yuelong Chi, Su Pang, Xiangpeng Wang, Qilin Huang

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DT-YOLO: An Improved Object Detection Algorithm for Key Components of Aircraft and Staff in Airport Scenes Based on YOLOv5 by Zhige He, Yuanqing He, Yang Lv

“…Based on YOLOv5, we propose an improved object detection algorithm, called DT-YOLO, to address these issues. …”
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Enhancing sentiment analysis in tourism reviews: A comparative study of algorithms in ASPECT-BASED SENTIMENT ANALYSIS and EMOTION DETECTION by Viktor Handrianus Pranatawijaya, Putu Bagus Adidyana Anugrah Putra, Ressa Priskila, Novera Kristianti

“…This research aims to combine Aspect-Based Sentiment Analysis (ABSA) and emotion detection for a more in-depth analysis of tourism reviews in Palangka Raya City and compare the performance of various algorithms. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…This assessment focuses on the use of software with artificial intelligence (AI)-derived algorithms to assist in the detection and analysis of lung nodules in CT chest scans. …”
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Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms by S. Jayanthi, Swathi Sowmya Bavirthi, P. Murali, K. Vijaya Kumar, Hend Khalid Alkahtani, Mohamad Khairi Ishak, Samih M. Mostafa

“…This paper proposes a Cybersecurity-Resource Exhaustion Attack Using Hybrid Deep Learning Model and Metaheuristic Optimizer Algorithms (CREA-HDLMOA) technique. The primary goal of the CREA-HDLMOA technique is to advance an effective method for DDoS attack detection using advanced optimization algorithms. …”
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A Fast Independent Component Analysis Algorithm for Geochemical Anomaly Detection and Its Application to Soil Geochemistry Data Processing by Bin Liu, Si Guo, Youhua Wei, Zedong Zhan

“…A fast independent component analysis algorithm (FICAA) is introduced to process geochemical data for anomaly detection. …”
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Advanced object detection for smart accessibility: a Yolov10 with marine predator algorithm to aid visually challenged people by Mahir Mohammed Sharif Adam, Hussah Nasser AlEisa, Samah Al Zanin, Radwa Marzouk

Subjects: “…Object detection…”
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A high maneuvering dim target detection algorithm based on non-uniform sub-aperture division and hybrid accumulation by LI Jiajia, TAO Haihong, WANG Le, QU Aopeng

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Whale Optimization Algorithm-Enhanced Long Short-Term Memory Classifier with Novel Wrapped Feature Selection for Intrusion Detection by Haider AL-Husseini, Mohammad Mehdi Hosseini, Ahmad Yousofi, Murtadha A. Alazzawi

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Pipeline Polluted Gas Leakage Detection in Chemical Parks Based on the Distributed Fiber Optic Sensing Data Fusion Algorithm by Peiwang Li, Kangxi Wang, Guanghui Sun, Liming Qin

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CTL-YOLO: A Surface Defect Detection Algorithm for Lightweight Hot-Rolled Strip Steel Under Complex Backgrounds by Wenzheng Sun, Na Meng, Longfa Chen, Sen Yang, Yuguo Li, Shuo Tian

“…Additionally, it exhibits strong generalization capabilities on the public dataset GC10-DET. The algorithm can effectively improve detection accuracy while maintaining a lightweight design.…”
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A Hybrid Genetic Algorithm with Tabu Search Using a Layered Process for High-Order QAM in MIMO Detection by Taehyoung Kim, Gyuyeol Kong

Subjects: “…MIMO detection…”
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URT-YOLOv11: A Large Receptive Field Algorithm for Detecting Tomato Ripening Under Different Field Conditions by Di Mu, Yuping Guou, Wei Wang, Ran Peng, Chunjie Guo, Francesco Marinello, Yingjie Xie, Qiang Huang

“…This study proposes an improved YOLOv11 model to address the limitations of traditional tomato recognition algorithms in complex agricultural environments, such as lighting changes, occlusion, scale variations, and complex backgrounds. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…It also requires fewer parameters and takes minimum training time. • The major contribution of this study is the design of an optimized, efficient and enhanced deep learning technique for multiclass rice crop disease detection embracing with batch normalization, dropout and genetic optimization algorithm to improve generalization power and restrict the overlearning capability for seen and unseen data. • Proposed VCNet, a shallow model with deep feature extraction, employs VGG16 layers for initial extraction fused with custom CNN architecture to correctly detect the challenging classes of diseases like sheath rot in multiclass classification. • The most significant observation is that VCNet accurately predicts the rice disease for each class of diseases under study whereas the existing powerful models largely misclassified for some classes of diseases in multiclass classification.…”
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