LSKAFF-YOLO: Large Separable Kernel Attentional Feature Fusion Network for Transmission Tower Detection in High-Resolution Satellite Remote Sensing Images by Xiaojin Yan, Zhixuan Li, Yongjie Zhai, Ke Liu, Ke Zhang, Zhenbing Zhao

“…This article addresses the challenges in detecting transmission towers, which are often obscured by complex backgrounds, variable object sizes, and small-scale objects. …”
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Identifying All Matches of a Rigid Object in an Input Image Using Visible Triangles by Abdullah N. Arslan

“…It has been suggested that for objects identifiable by their corners, every triangle formed by these corner points can serve as a reference for detecting other corner points. This approach enables effective rigid object detection, including partial matches. …”
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Computationally Enhanced UAV-Based Real-Time Pothole Detection Using YOLOv7-C3ECA-DSA Algorithm by Siti Fairuz Mat Radzi, Mohd Amiruddin Abd Rahman, Muhammad Khairul Adib Muhammad Yusof, Nurin Syazwina Mohd Haniff, Romi Fadillah Rahmat

“…Although YOLO-based algorithms have been widely adopted for their speed and efficiency in object detection, achieving a balance between high accuracy and low inference time remains a challenge, particularly in scenarios involving small objects and complex features. …”
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IEAM: Integrating Edge Enhancement and Attention Mechanism with Multi-Path Complementary Features for Salient Object Detection in Remote Sensing Images by Fubin Zhang, Zichi Zhang

“…To address these challenges, we integrate edge enhancement and attention mechanisms with multi-path complementary features for salient object detection in remote sensing images (IEAM), aiming to improve salient target accuracy, boundary detection, and memory efficiency. …”
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Red Raspberry Maturity Detection Based on Multi-Module Optimized YOLOv11n and Its Application in Field and Greenhouse Environments by Rongxiang Luo, Xue Ding, Jinliang Wang

“…In order to achieve accurate and rapid identification of red raspberry fruits in the complex environments of fields and greenhouses, this study proposes a new red raspberry maturity detection model based on YOLOv11n. …”
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A hybrid Bi-LSTM model for data-driven maintenance planning by Alexandros Noussis, Ryan O’Neil, Ahmed Saif, Abdelhakim Khatab, Claver Diallo

“…Abstract Modern industries dependent on reliable asset operation under constrained resources employ intelligent maintenance methods to maximize efficiency. However, classical maintenance methods rely on assumed lifetime distributions and suffer from estimation errors and computational complexity. …”
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A Low Computational Cost Method for Mobile Malware Detection Using Transfer Learning and Familial Classification Using Topic Modelling by Saket Acharya, Umashankar Rawat, Roheet Bhatnagar

“…In recent times, most researchers and scholars have used deep learning approaches to detect Android malware. Although deep learning techniques provide good accuracy and efficiency, they require high computational cost to train huge and complex data sets. …”
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Hybrid Naïve Bayes Models for Scam Detection: Comparative Insights From Email and Financial Fraud by Lebede Ngartera, Mahamat Ali Issaka, Saralees Nadarajah

“…Online scams continue to escalate in scale and sophistication, ranging from deceptive phishing emails to complex financial fraud schemes. These evolving threats have surpassed the capabilities of traditional detection systems, creating an urgent demand for scalable, real-time, and interpretable machine learning solutions. …”
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Parametric Analysis of Outrigger Systems for High-Rise Buildings with Different Geometric Shapes by Giulia Angelucci, Edoardo Cecca, Fabrizio Mollaioli

“…By providing quantifiable insights into outrigger performance in complex-shaped structures, this research guides a more integrated architectural and structural approach in contemporary high-rise construction, leveraging an efficient simplified modeling framework for preliminary design.…”
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Research on multi-view collaborative detection system for UAV swarms based on Pix2Pix framework and BAM attention mechanism by Yan Ding, Qingxin Cao, Bozhi Zhang, Peilin Li, Zhongjiao Shi

“…The system is designed to enhance multi-view image generation and detection algorithms, thereby improving the accuracy and efficiency of object detection across varying perspectives. …”
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Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detection of Bloomed Damask Roses in the Field by Farhad Fatehi, Hossein Bagherpour, Jafar Amiri Parian

“…Recent developments in deep learning algorithms, especially in convolutional models, have shown significant promise for object detection, highlighting strong possibilities for improving the efficiency of this process. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…However, sugarcane leaves and stalks intertwine and overlap at this stage. They can form a complex occlusion structure, which poses a greater challenge to target detection. …”
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Reducing heat stress damage in cereal crops through agronomic management and breeding strategies by Abu Bakar Siddique, Sergey Shabala, Chengdao Li, Zhong-Hua Chen, Rajeev K. Varshney, Chenchen Zhao, Meixue Zhou

“…However, with HS tolerance being a complex trait, breeding heat tolerant cultivars still face several challenges in cereal crops. …”
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Latency Analysis of UAV-Assisted Vehicular Communications Using Personalized Federated Learning with Attention Mechanism by Abhishek Gupta, Xavier Fernando

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Deep learning models for detection of explosive ordnance using autonomous robotic systems: trade-off between accuracy and real-time processing speed by Vadym Mishchuk, Herman Fesenko, Vyacheslav Kharchenko

“…The following results were obtained. 1) The results of a comparative analysis of YOLOv8 and RT-DETR models for EO detection in the context of speed-accuracy trade-offs. 2) Recommendations for EO detection model configurations aimed at improving the efficiency of autonomous demining robotic systems, including optimal camera parameter selection. 3) Methods for improving EO detection model performance to increase its accuracy in complex environments, including synthetic data generation and confidence threshold tuning. …”
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Supply Chain Management Control in the Aerospace Sector: An Empirical Approach by Gonzalo Torralba-Carnerero, Manuel García-Nieto, Juan Manuel Ramón-Jerónimo, Raquel Flórez-López

“…This is especially important given the complexity of aircraft manufacturing, the globalization of supply chains, and the requirement to meet stringent regulatory standards. …”
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Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans by Wisal Zafar, Ghassan Husnain, Abid Iqbal, Ali Saeed Alzahrani, Muhammad Abeer Irfan, Yazeed Yasin Ghadi, Mohammed S. AL-Zahrani, Ramasamy Srinivasaga Naidu

“…The integration of YOLOv8s and U-Net in Enhanced TumorNet offers a powerful solution for the automated analysis of brain tumors in MRI scans, significantly improving detection and segmentation accuracy. This hybrid approach holds great potential for clinical applications, enhancing the efficiency and effectiveness of brain tumor diagnosis.…”
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OculusNet: Detection of retinal diseases using a tailored web-deployed neural network and saliency maps for explainable AI by Muhammad Umair, Jawad Ahmad, Oumaima Saidani, Mohammed S. Alshehri, Alanoud Al Mazroa, Muhammad Hanif, Rahmat Ullah, Muhammad Shahbaz Khan

“…This study introduces OculusNet, an efficient and explainable deep learning (DL) approach for detecting retinal diseases using OCT images. …”
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Core elements for a smooth transition from laparoscopic to robotic colorectal surgery by Shuai Ma, Quanbo Zhou, Weitang Yuan, Yugui Lian

“…Moreover, previous laparoscopic experience has a limited effect on shortening the learning curve, while case selection and training volume are more crucial. Case selection should quantify the surgical difficulty through preoperative clinical parameters and follow the principle of “from simple to complex”. …”
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On-axis structured beams generation via moiré and Mie resonant metallo-dielectric moiré gratings by Anil Ringne, Subrata Karmakar, Ananth Krishnan

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