BCS_YOLO: Research on Corn Leaf Disease and Pest Detection Based on YOLOv11n by Shengnan Hao, Erjian Gao, Zhanlin Ji, Ivan Ganchev

“…Frequent corn leaf diseases and pests pose serious threats to agricultural production. Traditional manual detection methods suffer from significant limitations in both performance and efficiency. …”
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A Hybrid Graph-Based Risk Assessment and Attack Path Detection Model for IoT Systems by Ferhat Arat, Sedat Akleylek, Zaliha Yuce Tok

“…Our proposed approach targets high-vulnerability components within the system through risk-weighted backtracking, thereby facilitating more efficient attack path detection and filtering. The developed method is evaluated in a border security case scenario, with comparisons made in terms of algorithmic and asymptotic complexity. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…However, existing deep learning (DL) models often lack architectural adaptations for the visual complexities of UAV imagery, including low-texture contrast, noise interference, and irregular crack patterns. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Conclusions: This machine learning model provides an efficient and practical tool for detecting AAE using routine blood parameters, offering potential value in clinical practice, especially in resource-limited settings. …”
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Combining chromosome conformation capture and exome sequencing for simultaneous detection of structural and single-nucleotide variants by Maria Gridina, Timofey Lagunov, Polina Belokopytova, Nikita Torgunakov, Miroslav Nuriddinov, Artem Nurislamov, Lyudmila P. Nazarenko, Anna A. Kashevarova, Maria E. Lopatkina, Stanislav Vasilyev, Andrey Zuev, Elena O. Belyaeva, Olga A. Salyukova, Aleksandr D. Cheremnykh, Natalia N. Sukhanova, Marina E. Minzhenkova, Zhanna G. Markova, Nina A. Demina, Yana Stepanchuk, Anna Khabarova, Alexandra Yan, Emil Valeev, Galina Koksharova, Elena V. Grigor’eva, Natalia Kokh, Tatiana Lukjanova, Yulia Maximova, Elizaveta Musatova, Elena Shabanova, Andrey Kechin, Evgeniy Khrapov, Uliana Boyarskih, Oxana Ryzhkova, Maria Suntsova, Alina Matrosova, Mikhail Karoli, Andrey Manakhov, Maxim Filipenko, Evgeny Rogaev, Nadezhda V. Shilova, Igor N. Lebedev, Veniamin Fishman

“…Enhanced with targeted long-read sequencing, Exo-C evolves into a cost-efficient solution capable of resolving complex SVs at base-pair accuracy. …”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…We then combined bidirectional long short-term memory (BiLSTM), convolutional neural network, and the attention mechanism for vulnerability detection and classification. Additionally, our model includes a gated recurrent units memory module that enhances efficiency using historical execution data from the contract. …”
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Cross-modal interactive and global awareness fusion network for RGB-D salient object detection. by Runqing Li, Ling Yu, Zijian Jiang, Fanglin Niu

“…However, the existing RGB-D detection model still encounters difficulties in accurately recognising and highlighting salient objects when facing complex scenes containing multiple or small objects. …”
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A high precision YOLO model for surface defect detection based on PyConv and CISBA by Shufen Ruan, Chenmei Zhan, Bo Liu, Quan Wan, Kunfang Song

“…Abstract Defect detection is vital for product quality in industrial production, yet current surface defect detection technologies struggle with diverse defect types and complex backgrounds. …”
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Vehicle Flow Detection and Tracking Based on an Improved YOLOv8n and ByteTrack Framework by Jinjiang Liu, Yonghua Xie, Yu Zhang, Haoming Li

“…These enhancements significantly boost the model’s ability to detect small objects and handle complex backgrounds. …”
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A Tactical Conflict Detection and Resolution Method for En Route Conflicts in Trajectory-Based Operations by Dong Sui, Kai Zhang

“…In the conflict detection (CD) submodule, a spatial data structure with low time complexity, the R tree algorithm, is used. …”
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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…Abstract Object detection in remote sensing imagery presents challenges due to low resolution, complex backgrounds, occlusions, and scale variations, which are critical in disaster response, environmental monitoring, and surveillance. …”
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Advancing Software Vulnerability Detection with Reasoning LLMs: DeepSeek-R1′s Performance and Insights by Wenting Qin, Lijie Suo, Liangchen Li, Fan Yang

“…The increasing complexity of software systems has heightened the need for efficient and accurate vulnerability detection. …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…Differing from traditional and often expensive or complex detection methods, our approach utilizes a low-cost antipodal Vivaldi antenna, complemented by a custom-designed defect rate detection system. …”
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Automatic Detection of Landslide Surface Cracks from UAV Images Using Improved U-Network by Hao Xu, Li Wang, Bao Shu, Qin Zhang, Xinrui Li

“…Surface cracks are key indicators of landslide deformation, crucial for early landslide identification and deformation pattern analysis. However, due to the complex terrain and landslide extent, manual surveys or traditional digital image processing often face challenges with efficiency, precision, and interference susceptibility in detecting these cracks. …”
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MonoAMP: Adaptive Multi-Order Perceptual Aggregation for Monocular 3D Vehicle Detection by Xiaoxi Hu, Tao Chen, Wentao Zhang, Guangyi Ji, Hongxia Jia

“…Monocular 3D object detection is rapidly emerging as a key research direction in autonomous driving, owing to its resource efficiency and ease of implementation. …”
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Optimizing concrete crack detection an echo state network approach with improved fish migration optimization by Zhichun Fang, Xiuhong Wang, Jiaojiao Gao, Behrooz Eskandarpour

“…However, there are many models available for concrete crack detection, an efficient approach is needed because the existing methods often have flaws like overfitting, high computational complexity, and noise sensitivity, which can lead to accurate crack detection and classification. …”
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The application of deep learning technology in smart agriculture: Lightweight apple leaf disease detection model by Luo Man

“…These advancements make it robust, efficient, and practical for real-time disease detection in intelligent agricultural environments.…”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…Simulation results confirm that the DTHC method achieves a spectrum hole detection accuracy of 99%, with a miss-detection probability below 0.9%, demonstrating its effectiveness in enhancing CRN performance while maintaining low complexity.…”
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Efficiently Modeling Lateral Vehicle Movement Including its Temporal Interrelations Using a Two-Level Stochastic Model by N. Neis, J. Beyerer

“…It is shown that the model allows for efficient calibration, is able to replicate the behavior of these drivers, and is characterized by short runtimes. …”
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Rapid and Efficient Screening of <i>Helicobacter pylori</i> in Gastric Samples Stained with Warthin–Starry Using Deep Learning by José Aneiros-Fernández, Pedro Montero Pavón, Natalia García Gómez, Rosa María Palo Prian, Ismael Sánchez García, Ana Isabel Romero Ortiz, Rodrigo López Castro, César Casado-Sánchez, Víctor Sánchez Turrión, Antonio Luna, Manuel Álvaro Berbís

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