Real-Time Forest Fire Detection with Lightweight CNN Using Hierarchical Multi-Task Knowledge Distillation by Ismail El-Madafri, Marta Peña, Noelia Olmedo-Torre

“…The novelty of this approach lies in leveraging knowledge distillation to transfer the deeper insights learned by the DenseNet201 teacher model—specifically, the auxiliary task of recognizing the confounding elements responsible for false positives—into a lightweight student model, enabling it to achieve a similar robustness without the need for complex architectures. Using this distilled knowledge, we trained a MobileNetV3-based student model, which was designed to operate efficiently in real-time while maintaining a low computational overhead. …”
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FGA-Corn: an integrated system for precision pesticide application in center leaf areas using deep learning vision by Zhongqiang Song, Zhongqiang Song, Wenqiang Li, Xuehang Song, Shun Li

“…The third part is the GMA-YOLOv8 detection algorithm for center leaf areas. Building on the YOLOv8n framework, a more efficient GHG2S backbone generated by HGNetV2 enhanced with GhostConv and SimAM is proposed for feature extraction. …”
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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 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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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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Role of ^99mTc-pyrophosphate myocardial scintigraphy in assessing the efficiency of tafamidis therapy: a case series by A. A. Shoshina, A. A. Ansheles, S. N. Nasonova, I. V. Zhirov, V. B. Sergienko, S. N. Tereshchenko

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VMMCD: VMamba-Based Multi-Scale Feature Guiding Fusion Network for Remote Sensing Change Detection by Zhong Chen, Hanruo Chen, Junsong Leng, Xiaolei Zhang, Qi Gao, Weiyu Dong

“…Moreover, the former also leads to a reduction in speed. To guarantee the efficiency of change detection, encompassing both speed and accuracy, a VMamba-based Multi-scale Feature Guiding Fusion Network (VMMCD) is proposed. …”
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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints.…”
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A Full-Scale Shadow Detection Network Based on Multiple Attention Mechanisms for Remote-Sensing Images by Lei Zhang, Qing Zhang, Yu Wu, Yanfeng Zhang, Shan Xiang, Donghai Xie, Zeyu Wang

“…Therefore, this model offers an efficient solution for shadow detection in aerial imagery.…”
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A Real-Time Cotton Boll Disease Detection Model Based on Enhanced YOLOv11n by Lei Yang, Wenhao Cui, Jingqian Li, Guotao Han, Qi Zhou, Yubin Lan, Jing Zhao, Yongliang Qiao

“…Existing methods for detecting cotton boll diseases frequently exhibit high rates of <b>both</b> false negatives and false positives under complex field conditions (e.g., lighting variations, shadows, and occlusions) and struggle to achieve real-time performance on edge devices. …”
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LIU-NET: lightweight Inception U-Net for efficient brain tumor segmentation from multimodal 3D MRI images by Gul e Sehar Shahid, Jameel Ahmad, Chaudary Atif Raza Warraich, Amel Ksibi, Shrooq Alsenan, Arfan Arshad, Rehan Raza, Zaffar Ahmed Shaikh

“…Its capability to efficiently and precisely segment brain tumors, especially in challenging-to-detect regions, distinguishes it from existing models. …”
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Design, construction and efficiency analysis of bagasse-based charcoal packed horizontal lab-scale wetland for the removal of antibiotic-resistant bacteria by Misbah Batool Aslam, Talmeez U. R. Rehman, Amina Farrukh Alavi, Abdul Haleem, Abdul Haq, Safia Ahmed, Wasim Sajjad, Mohammed Bourhia, Ousman B. Mahamat, Khalid S. Almaary, Mahwish Ali

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Tomato yellow leaf curl virus detection based on cross-domain shared attention and enhanced BiFPN by Henghui Mo, Linjing Wei

“…This model exhibits exceptional performance in detecting TYLCV in complex environments, providing robust technical support for tomato growth monitoring and offering insights for the detection of other crop diseases. …”
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Quality and reliability of IFC/BIM models for public educational facilities construction projects via clash detection by Michał Juszczyk, Mantas Vaišnoras, Robertas Kontrimovičius, Tomáš Hanák, Hanna Łukaszewska, Leonas Ustinovichius

“…A mixed-methods approach was employed to analyse the number, types, and geometric characteristics of detected clashes. The research introduces innovative metrics, such as the Relative Quality Coefficient (RQC), Relative Uncertainty Coefficient (RUC), and Modified Relative Quality Coefficient (MRQC), to assess model quality and reliability quantitatively. …”
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Detection, Isolation, and Identification of Multiplicative Faults in a DC Motor and Amplifier Using Parameter Estimation Techniques by Sanja Antić, Marko Rosić, Branko Koprivica, Alenka Milovanović, Milentije Luković

“…The increasing complexity of modern control systems highlights the need for reliable and robust fault detection, isolation, and identification (FDII) methods, particularly in safety-critical and industrial applications. …”
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Machine Learning-Based Attack Detection and Mitigation with Multi-Controller Placement Optimization over SDN Environment by Binod Sapkota, Arjun Ray, Manish Kumar Yadav, Babu R. Dawadi, Shashidhar R. Joshi

“…Additionally, the IDS decouples from the controllers, preserves controller resources, and allows for efficient near-real-time attack detection and mitigation. …”
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Fractional Artificial Protozoa Optimization Enabled Deep Learning for Intrusion Detection and Mitigation in Cyber-Physical Systems by Shaik Abdul Rahim, Arun Manoharan

“…Thereafter, intrusion detection is carried out with Spiking VGG-16. Lastly, attack classification is accomplished utilizing Spiking VGG-16 trained by FAPO, and then attack mitigation is detected. …”
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Design and implementation of a 100 kVA transformer monitoring and fault detection system for distribution network by Charity M. Nkinyam, Leo Tanyam Encho, Nfah Eustace Mbaka

“…Abstract The increasing complexity of today’s power distribution networks requires reliable and intelligent monitoring and maintenance systems, especially as the demand for electricity increases due to technological and population growth. …”
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An optimized anomaly detection framework in industrial control systems through grey wolf optimizer and autoencoder integration by Muhammad Muzamil Aslam, Liyanage Chandratilak De Silva, Rosyzie Anna Awg Haji Mohd Apong, Ali Tufail

“…Abstract Ensuring reliable Internet connectivity in Industrial Control Systems is critical for real-time monitoring and anomaly detection. Existing methods, however, struggle with high computational complexity, limited applicability to specific datasets, and elevated false-positive rates. …”
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CD-STMamba: Toward Remote Sensing Image Change Detection With Spatio-Temporal Interaction Mamba Model by Shanwei Liu, Shuaipeng Wang, Wei Zhang, Tao Zhang, Mingming Xu, Muhammad Yasir, Shiqing Wei

“…Change detection (CD) is a critical Earth observation task. …”
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