Efficient Complex Event Processing over RFID Streams by Kyoung Soo Bok, Myung Ho Yeo, Byoung Yeop Lee, Jae Soo Yoo

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Low-Complexity Gaussian Detection for MIMO Systems by Tianbin Wo, Peter Adam Hoeher

“…Using factor graphs as a general framework and applying the Gaussian approximation, three low-complexity iterative detection algorithms are derived, and their performances are compared by means of Monte Carlo simulations. …”
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Complex Indoor Human Detection with You Only Look Once: An Improved Network Designed for Human Detection in Complex Indoor Scenes by Yufeng Xu, Yan Fu

“…However, the complex indoor environment and background pose challenges to the detection task. …”
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An efficient fusion detector for road defect detection by Li Yang, Jingwei Deng, Hailong Duan, Chenchen Yang

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Potato late blight leaf detection in complex environments by Jingtao Li, Jiawei Wu, Rui Liu, Guofeng Shu, Xia Liu, Kun Zhu, Changyi Wang, Tong Zhu

“…Abstract Potato late blight is a common disease affecting crops worldwide. To help detect this disease in complex environments, an improved YOLOv5 algorithm is proposed. …”
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Enhanced YOLOv8 with lightweight and efficient detection head for for detecting rice leaf diseases by Bo Gan, Guolin Pu, Weiyin Xing, Lianfang Wang, Shu Liang

“…While YOLO object detection algorithms show strong performance in automated detection, their feature extraction capabilities remain limited in complex agricultural settings. …”
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Efficient detection and counting method for maize seedling plots by Feiyun Wang, Hanlu Jiang, Jincan Wu, Fupeng Li, Bo Zhao, Wenhua Mao, Chengxu Lv, Liming Zhou, Qingzhong Xu

“…To efficiently detect and count maize seedlings in complex field conditions, this study first developed a sample dataset under diverse backgrounds and lighting scenarios and introduced a data augmentation technique called “M_AUG.” …”
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A YOLO-Based Method for Head Detection in Complex Scenes by Ming Xie, Xiaobing Yang, Boxu Li, Yingjie Fan

“…This paper introduces a novel head detection algorithm, YOLO-Based Head Detection in Complex Scenes (YOLO-HDCS). …”
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Advanced Self-Driving Vehicle Model for Complex Road Navigation Using Integrated Image Processing and Sensor Fusion by Kalapraveen Bagadi, Naveen Kumar Vaegae, Visalakshi Annepu, Khaled Rabie, Shafiq Ahmad, Thokozani Shongwe

“…The model integrates state-of-the-art image processing techniques with advanced sensor fusion, utilizing EfficientDet D0 and Haar Cascade object detection models to identify obstacles, road signs, and traffic signals accurately. …”
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Lightweight Detection Methods for Multi-Scale Targets in Complex Scenarios by Anjun Yu, Zhichao Rao, Yonghua Xiong, Jinhua She

“…Detecting multi-scale objects in complex scenes is crucial for real-time applications in building safety, where accurate monitoring of safety equipment under challenging conditions is essential. …”
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Direct detection with an optimal transfer function: toward the electrical spectral efficiency of coherent homodyne detection by Xingfeng Li, Jingchi Li, Xiong Ni, Hudi Liu, Qunbi Zhuge, Haoshuo Chen, William Shieh, Yikai Su

“…Complex-valued double-sideband direct detection (DD) can reconstruct the optical field and achieve a high electrical spectral efficiency (ESE) comparable to that of a coherent homodyne receiver, and DD does not require a costly local oscillator laser. …”
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Relationship-Based Ambient Detection for Concrete Pouring Verification: Improving Detection Accuracy in Complex Construction Environments by Seungwon Yang, Hyunsoo Kim

“…However, traditional monitoring methods face limitations such as overlapping objects, environmental similarities, and detection errors caused by ambiguous boundaries. This study proposes an Ambient Detection-based Monitoring Framework that enhances object detection by incorporating contextual relationships between objects in complex construction environments. …”
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BGM-YOLO: An accurate and efficient detector for detecting plant disease. by Chenghai Yu, Junhao Xie, Fernandes Jean Adrian Tony

“…The experimental results demonstrate that the BGM-YOLO model achieves a 3.9% improvement in the mean average precision (mAP) over the original model. In crop disease detection tasks, the BGM-YOLO model has higher detection accuracy and a lower false negative rate, confirming its practical value in complex application scenarios.…”
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An Efficient Group Convolution and Feature Fusion Method for Weed Detection by Chaowen Chen, Ying Zang, Jinkang Jiao, Daoqing Yan, Zhuorong Fan, Zijian Cui, Minghua Zhang

“…Currently, research on vegetable weed detection technology is relatively limited, and existing detection methods still face challenges due to complex natural conditions, resulting in low detection accuracy and efficiency. …”
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Evaluating the Capture Efficiency of Microchannel Plates Through Photoelectron Detection by Mutong Wu, Lingmin Ye, Shangtong Li, Xuan Zhao, Hua Cai, Quan Yu

“…Capture efficiency (CE) is a critical performance parameter for microchannel plates (MCPs), yet its accurate measurement remains challenging. …”
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The influence of detector's parameters on the efficiency of radio signals with complex phase modulation receiving by I. P. Maksymiv, S. І. Altunin, A. P. Bondariev, I. V. Horbatyi

“…The second part of the work was dedicated to the research of detection efficiency of modified detector using complex phase modulated signal 8-QAM. …”
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Enhancing the efficiency of the use of complex pathomorphological studies for the timely diagnostics of mycosis fungoides by N. V. Kungurov, G. D. Safonova, M. M. Kokhan, O. G. Rimar, I. A. Kuklin

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Small Target Detection for Power Line Components in Complex UAV Imagery by Zhiyuan Sun, Xu Wang

“…To address the limitations of existing algorithms—particularly their low efficiency in detecting small objects and poor accuracy in complex backgrounds—we propose a defect detection model for transmission line components based on YOLOv5. …”
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Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…To address these limitations, this study introduces Mamba RT-DETR (MRD), an optimized architecture featuring three principal innovations: (1) We devise an efficient vehicle detection Mamba (EVDMamba) network that strategically integrates a linear-complexity state space model (SSM) to substantially mitigate computational overhead while preserving feature extraction efficacy. (2) To counteract the constrained receptive fields and suboptimal spatial localization associated with conventional SSM sequence modeling, we implement a multi-branch collaborative learning framework that synergistically optimizes channel dimension processing, thereby augmenting the model’s capacity to capture critical spatial dependencies. (3) Comprehensive evaluations on the BDD100K benchmark demonstrate that MRD architecture achieves a 3.1% enhancement in mean average precision (mAP) relative to state-of-the-art RT-DETR variants, while concurrently reducing parameter count by 55.7%—a dual optimization of accuracy and efficiency.…”
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