A comprehensive systematic review of intrusion detection systems: emerging techniques, challenges, and future research directions by Arjun Kumar Bose Arnob, Rajarshi Roy Chowdhury, Nusrat Alam Chaiti, Sudipta Saha, Ajoy Roy

“… The role of Intrusion Detection Systems (IDS) in the protection against the increasing variety of cybersecurity threats in complex environments, including the Internet of Things (IoT), cloud computing, and industrial networks. …”
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SDFSD-v1.0: A Sub-Meter SAR Dataset for Fine-Grained Ship Detection by Peixin Cai, Bingxin Liu, Peilin Wang, Peng Liu, Yu Yuan, Xinhao Li, Peng Chen, Ying Li

“…In the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship detection, with dataset quality as a crucial factor influencing detection accuracy. …”
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Rotation-Invariant Feature Enhancement with Dual-Aspect Loss for Arbitrary-Oriented Object Detection in Remote Sensing by Zhao Hu, Xiangfu Meng, Xinsong Liu, Zhuxiang Sun

“…Evaluated on the DIOR-R and HRSC2016 benchmarks, our method demonstrates robust detection capabilities for arbitrarily oriented objects, achieving competitive performance in both accuracy and efficiency. …”
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R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals by Kamirul Kamirul, Odysseas A. Pappas, Alin M. Achim

“…This unified design improves efficiency by eliminating redundant computation inherent in separate pooling. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…The CBAM attention mechanism is added to the model to improve the extraction of subtle features of lesions in complex environments. Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. …”
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Development of eco-friendly and cost-effective electrochemical sensor for the simultaneous detection of 4-aminophenol and paracetamol in water by Antía Fdez-Sanromán, Najib Ben Messaoud, Marta Pazos, Emilio Rosales, Raquel Barbosa Queirós

“…It was successfully tested in real freshwater samples, demonstrating high accuracy even in complex matrices. This innovative methodology provides a rapid, cost-effective, and portable analytical tool for routine monitoring of pharmaceutical contaminants, enabling more accurate environmental risk assessments and supporting the implementation of more efficient management strategies.…”
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Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications by Mingzhe Lyu, Helin Gong, Zhang Chen, Jiangyu Wang, Mingxiao Zhong, Zhiyong Wang, Qing Li, Zefei Pan

“…For fault diagnosis, the dual-monitoring system reduces the false negative rate to 18.73% and improves recall to 81.27%, demonstrating strong anomaly detection under complex conditions. By combining short-term fluctuation sensitivity with long-term trend stability, the proposed approach offers a robust and generalizable solution for intelligent monitoring. …”
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ASIC Design for Real-Time CAN-Bus Intrusion Detection and Prevention System Using Random Forest by Junseok Lee, Sangmin Park, Sua Shin, Hyungchul Im, Joosock Lee, Seongsoo Lee

“…To address this issue, we designed an IDS that can immediately determine if an attack is present when receiving a CAN frame and blocking the attack node. Fast and efficient detection is possible complex matrix operations because the random forest model performs detection based on comparison operations. …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…The presented MCOBC-HDDC method provides an efficient and accurate disease diagnosis, utilizing a system that depends on DL techniques. …”
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Multiple Targets CFAR Detection Performance Based on an Intelligent Clustering Algorithm in K-Distribution Sea Clutter by Mansoor M. Al-dabaa, Eugen Laslo, Ahmed A. Emran, Ahmed Yahya, Ashraf Aboshosha

“…It is noteworthy that the proposed method achieves detection performance comparable to the more computationally intensive DBSCAN-CFAR while significantly reducing computational complexity. …”
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Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments by G. Nalinipriya, S. Rama Sree, K. Radhika, E. Laxmi Lydia, Faten Khalid Karim, Mohamad Khairi Ishak, Samih M. Mostafa

“…Machine learning (ML) plays a crucial role in cybersecurity by making malware detection more scalable, efficient, and automated, reducing reliance on conventional human intervention methods. …”
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Research on Blueberry Maturity Detection Based on Receptive Field Attention Convolution and Adaptive Spatial Feature Fusion by Bingqiang Huang, Zongyi Xie, Hanno Homann, Zhengshun Fei, Xinjian Xiang, Yongping Zheng, Guolong Zhang, Siqi Sun

“…Detecting small objects in complex outdoor conditions remains challenging. …”
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YOLO-Tryppa: A Novel YOLO-Based Approach for Rapid and Accurate Detection of Small Trypanosoma Parasites by Davide Antonio Mura, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto

“…Early detection of Trypanosoma parasites is critical for the prompt treatment of trypanosomiasis, a neglected tropical disease that poses severe health and socioeconomic challenges in affected regions. …”
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Research progress on the application of RPA-CRISPR/Cas12a in the rapid visual detection of pathogenic microorganisms by Tuo Ji, Tuo Ji, Tuo Ji, Xin Fang, Yuzhi Gao, Yuzhi Gao, Yuzhi Gao, Kun Yu, Kun Yu, Kun Yu, Xuzhu Gao, Xuzhu Gao, Xuzhu Gao

“…In an increasingly complex global public health landscape, the continuous emergence of novel pathogens and the growing problem of antibiotic resistance highlight the urgent need for rapid, efficient, and precise detection technologies for pathogenic microorganisms. …”
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CUNet-CLSTM: A Novel Fusion of CUNet and CLSTM for Superior Liver Cancer Detection in CT Scans by K. Vijayaprabakaran, Padmanaban Ramalingam, Rajakumar Ramalingam, A. Ilavendhan, R. Vedhapriyavadhana

“…Despite the triumph of convolutional neural networks in medical image analysis, challenges such as overfitting, limited labeled data, and complex tumor morphology hinder accurate detection of liver cancer. …”
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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

“…To tackle the challenge of wake waves from moving ships obscuring small targets, we introduce a gradient flow mechanism that improves detection efficiency under dynamic conditions. The Tail Wave Detection Method synergistically integrates gradient computation with target detection techniques. …”
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A Dual-Branches Multiscale Dynamic Partial Convolutional Attention Network for Remote Sensing Change Detection by Wenbin Tang, Shuli Cheng, Anyu Du

“…In addition, a bottom-up training strategy is applied to strengthen the completeness of change detection. Extensive experiments on three publicly available datasets demonstrate that, compared to other methods, our proposed approach achieves superior performance and detection results, while reducing parameters and computational complexity.…”
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Real-time driver drowsiness detection using transformer architectures: a novel deep learning approach by Osama F. Hassan, Ahmed F. Ibrahim, Ahmed Gomaa, M. A. Makhlouf, B. Hafiz

“…This represents a significant advancement over existing methods, demonstrating the effectiveness of transformer-based architectures in capturing complex spatial dependencies and extracting relevant features for drowsiness detection. …”
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Universal Method for Detecting Violations in the Integrity of a Digital Image Based on Analysis of Blocks of its Matrix by Bobok I., Kobozeva A.

“…Thus, the aim of the work is to increase the efficiency of identifying the fact of violation of image integrity by developing a universal expert method with low computational complexity. …”
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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

“…Abstract With the advancement of medical technology, a large amount of complex data on cancers is produced for diagnosing and treating cancers. …”
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