CSF-YOLO: A Lightweight Model for Detecting Grape Leafhopper Damage Levels by Chaoxue Wang, Leyu Wang, Gang Ma, Liang Zhu

“…The model employs FasterNet as the backbone network to enhance computational efficiency and reduce model complexity. It substitutes for the nearest-neighbor upsampling with CARAFE to improve small target detection capabilities. …”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…The multicore initiator module C2f_PKI is employed to replace C2f as the Backbone network to accelerate target detection and reduce model complexity. By incorporating FDPN and DASI fusion modules into the Head module section, the aim is to reduce model complexity and enhance detection accuracy. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The unique characteristics of 5G networks, while enabling advanced communication, present challenges in distinguishing between legitimate and malicious traffic, making it more difficult to detect anonymous traffic. Current methodologies for intrusion detection within 5G communication exhibit limitations in accuracy, efficiency, and adaptability to evolving network conditions. …”
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Detection of weeds in vegetables using image classification neural networks and image processing by Huiping Jin, Kang Han, Kang Han, Hongting Xia, Bo Xu, Xiaojun Jin

“…However, the wide variety of weed types and their complex distribution creates difficulties in rapid and accurate weed detection. …”
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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…It has two primary types: one-stage detectors known for their high speed and efficiency, and two-stage detectors, which offer higher accuracy but are often slower due to their complex architecture. …”
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AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…However, traditional machine vision and deep learning approaches face notable challenges in complex underwater environments due to issues such as light attenuation, scattering, motion blur, color distortion, noise, low contrast, and multipath effects, which severely affect detection accuracy. …”
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RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection by Zhong Wang, Lanfang Lei, Tong Li, Xian Zu, Peibei Shi

“…Unlike generic object detection, smoke detection faces unique challenges due to smoke’s semitransparent, fluid nature, which often leads to false positives in complex backgrounds and missed detections—particularly around smoke edges and small targets. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…Compared with existing detection methods, this approach shows outstanding performance in detection accuracy, localization precision, and computational efficiency, particularly excelling in small object detection.…”
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An Image-Free Single-Pixel Detection System for Adaptive Multi-Target Tracking by Yicheng Peng, Jianing Yang, Yuhao Feng, Shijie Yu, Fei Xing, Ting Sun

“…Conventional vision-based sensors face limitations such as low update rates, restricted applicability, and insufficient robustness in dynamic environments with complex object motions. Single-pixel tracking systems offer high efficiency and minimal data redundancy by directly acquiring target positions without full-image reconstruction. …”
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A parallel algorithm for network traffic anomaly detection based on Isolation Forest by Xiaoling Tao, Yang Peng, Feng Zhao, Peichao Zhao, Yong Wang

“…With the rapid development of large-scale complex networks and proliferation of various social network applications, the amount of network traffic data generated is increasing tremendously, and efficient anomaly detection on those massive network traffic data is crucial to many network applications, such as malware detection, load balancing, network intrusion detection. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…However, dense planting patterns and complex environments within greenhouses present challenges for accurately detecting growth stages. …”
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Research on detection of wheat tillers in natural environment based on YOLOv8-MRF by Min Liang, Yuchen Zhang, Jian Zhou, Fengcheng Shi, Zhiqiang Wang, Yu Lin, Liang Zhang, Yaxi Liu

“…To bolster agricultural efficiency and precision, this study introduces the YOLOv8-MRF model (multi-path coordinate attention, receptive field attention convolution, and Focaler-CIoU-optimized YOLOv8), a groundbreaking advancement in automated detection of wheat tillers. …”
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CIDNet: A Maritime Ship Detection Model Based on ISAR Remote Sensing by Fei Liu, Boyang Liu, Hang Zhou, Song Han, Kunlin Zou, Wenjie Lv, Chang Liu

“…The model is based on the Boundary Box Efficient Transformer (BETR) architecture, which combines super-resolution preprocessing, a deep feature extraction network, a feature fusion technique, and a coordinate maintenance mechanism to improve the detection accuracy and real-time performance of ship targets in complex settings. …”
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A Multi-Domain Feature Fusion CNN for Myocardial Infarction Detection and Localization by Yunfan Chen, Jinxing Ye, Yuting Li, Zhe Luo, Jieqiang Luo, Xiangkui Wan

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Double-layer membrane framework-based gold microelectrode for determination of natural labile copper in complex water environments by Xinyue Hu, Haitao Han, Shanshan Wang, Dawei Pan

“…However, the determination of low concentration labile Cu (CuLabile) in complex water environments remains a huge challenge. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…Existing models have high false and missed detection rates in complex weather and multi-scale equipment scenarios. …”
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An image processing technique for optimizing industrial defect detection using dehazing algorithms. by Xuanyi Zhao, Xiaohan Dou, Gengpei Zhang

“…In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. …”
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Complex PM2.5 Pollution and Hospital Admission for Respiratory Diseases over Big Data in Cloud Environment by Yi Zhou, Lianshui Li

“…Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…This often leads to increased computational overhead and heightened complexity in detection models, potentially degrading overall system performance and efficiency. …”
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AN ITERATIVE ALGORITHM OF OBJECT DETECTION IN VIDEO SEQUENCE BASED ON HISTOGRAM SPATIAL MEASURES by I. A. Baryskievic

“…The parameters of algorithm are defined in terms of detection efficiency and computational complexity.…”
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