BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…Because these methods can automatically extract meaningful features from data and efficiently learn complex relationships, they can achieve better performance in malware detection as well as in solving many other problems. …”
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Optimized Error Detection and Correction in ATM Networks Using the Enhanced Berlekamp Massey Algorithm With Hybrid Automatic Repeat Request by Mahmut Aykac

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Multi-Modal Dynamic Fusion for Defect Detection in Electronic Products: A Novel Approach Based on Energy and Deep Learning by Yulin Liu, Yang Gao

“…Conventional defect detection approaches, which typically depend on a single modality, often fall short in both efficiency and reliability. …”
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A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction by Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana

“…This hybrid approach addresses class imbalance and high-dimensionality challenges, providing scalable and robust intrusion detection. Complexity analysis reveals that the proposed model reduces training and prediction times, making it suitable for real-time applications.…”
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Proposal for an Intelligent Methodology to Manage Energy in Buildings and Detect Anomalies as a Compass Towards Zero Energy Buildings (ZEB) by Irati Prol-Godoy, Roberto Santana, Francisco-Javier Rey-Martinez, Ana Picallo-Perez

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A Small-Sample Target Detection Method of Side-Scan Sonar Based on CycleGAN and Improved YOLOv8 by Ye Zheng, Jun Yan, Junxia Meng, Ming Liang

“…Because of their low cost and ease of deployment, side-scan sonars is one of the most widely used underwater survey instruments. However, the complexity of the marine environment and the difficulty in target acquisition limit the detection accuracy of side-scan sonars. …”
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A Semi-Supervised Diffusion-Based Framework for Weed Detection in Precision Agricultural Scenarios Using a Generative Attention Mechanism by Ruiheng Li, Xuaner Wang, Yuzhuo Cui, Yifei Xu, Yuhao Zhou, Xuechun Tang, Chenlu Jiang, Yihong Song, Hegan Dong, Shuo Yan

“…The development of smart agriculture has created an urgent demand for efficient and accurate weed recognition and detection technologies. …”
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Secure Quantum Communication With Multi-Users in Quantum Networks by As'Ad Mahmoud As'Ad Alnaser, Hazem Moh'D Said Hatamleh, Nawaf Abdualziz Almolhis, Salahaldeen Duraibi, Yahya Alqahtani

“…The performance of the system has been analyzed with metrics like detection accuracy of eavesdrop attack (97%), communication complexity (95%), effective key rate (590 b/s), communication efficiency (96%), and computational overhead (98%). …”
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Enhanced the Trans‐Cleavage Activity of CRISPR‐Cas12a Using Metal‐Organic Frameworks as Stimulants for Efficient Electrochemical Sensing of Circulating Tumor DNA by Shuai Wu, Yincheng Liu, Tianyu Zeng, Tianci Zhou, Yanting Sun, Ying Deng, Juan Zhang, Genxi Li, Yongmei Yin

“…Herein, an electrochemical biosensor based on manganese metal‐organic frameworks (MOFs)‐enhanced CRISPR (MME‐CRISPR) is proposed that enables the efficient detection of circulating tumor DNA (ctDNA). …”
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Towards precision diagnosis: a novel hybrid DC-CAD model for lung disease detection leveraging multi-scale capsule networks and temporal dynamics by Esther Stacy E. B. Aggrey, Qin Zhen, Seth Larweh Kodjiku, Linda Delali Fiasam, Collins Sey, Chiagoziem C. Ukwuoma, Evans Aidoo, Emmanuel Osei-Mensah

“…Abstract The early detection of lung diseases, including cancer, is essential for improving patient outcomes. …”
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Enhancing Pest Detection: Assessing Tuta absoluta (Lepidoptera: Gelechiidae) Damage Intensity in Field Images through Advanced Machine Learning by Edwin Lewıs, Atilla Erdinç, Yavuz Selim Şahin, Alperen Kaan Bütüner, Hilal Erdoğan

“…The integration of DTs in such applications, due to their unique ability to handle complex and indistinct shapes without the need for feature extraction, sets the stage for a new era of efficient and effective pest control strategies.…”
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Implementation Of Deep Learning Using Convolutional Neural Network Method In A Rupiah Banknote Detection System For Those With Low Vision by Dinul Akhiyar, Tukino Tukino, Sarjon Defit

“…The application of deep learning in various sectors continues to grow due to its ability to provide efficient and effective solutions to complex problems. …”
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Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

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GradCAM-PestDetNet: A deep learning-based hybrid model with explainable AI for pest detection and classification by Ramitha Vimala, Saharsh Mehrotra, Satish Kumar, Pooja Kamat, Arunkumar Bongale, Ketan Kotecha

“…The growing global population demands an efficient pest detection system to ensure food security. …”
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Enhanced YOLOv7-Tiny for Small-Scale Fire Detection via Multi-Scale Channel Spatial Attention and Dynamic Upsampling by Shihao Wu, Yi Xia

“…Fire detection remains a challenging task, particularly in distinguishing small smoke and flames from complex backgrounds. …”
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One-Step Rapid Detection of Histamine in Fish Using a Colorimetric Aptasensor Based on Magnetic Metal Organic Framework Nanozymes by QIU Yixing, LIU Xin, SONG Yufan, DING Yuting, XU Xia

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Anomaly Detection and Remaining Useful Life Prediction for Turbofan Engines with a Key Point-Based Approach to Secure Health Management by Yuntao Duan, Tao Zhang, Dunhuang Shi

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YOLO-RWY: A Novel Runway Detection Model for Vision-Based Autonomous Landing of Fixed-Wing Unmanned Aerial Vehicles by Ye Li, Yu Xia, Guangji Zheng, Xiaoyang Guo, Qingfeng Li

“…The results indicate that the proposed YOLO-RWY model possesses strong generalization and real-time capabilities, enabling accurate runway detection in complex and challenging visual environments, and providing support for the onboard VAL systems of fixed-wing UAVs.…”
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T-blocker: a simple and robust probe-free quantitative PCR assay to detect somatic mutations down to 0.1% frequency by Hanyoup Kim, Aaron E Ruby, Harini G Shandilya, Arvind K Virmani, Nandita Rahman, Christina M Strange, Jarkko Huuskonen

“…Highly efficient and specific mutant amplification in conjunction with selective wild-type suppression by the T-blocker concept enabled 0.1% detection sensitivity using the intercalating dye-based qPCR chemistry instead of more complex target-specific dye-labeled probes. …”
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Design of a plasmonic optical biosensor based on a metal-insulator-metal ring resonator for the detection of various bacterial pathogens by Ali Khodaie, Yousef Rafighirani, Hamid Heidarzadeh, Javad Javidan

“…By addressing key limitations in sensitivity and specificity in complex biological environments, this MIM-based sensor offers a robust platform for rapid, high-throughput bacterial detection in clinical diagnostics and beyond.…”
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