YOLOv8-MFD: An Enhanced Detection Model for Pine Wilt Diseased Trees Using UAV Imagery by Hua Shi, Yonghang Wang, Xiaozhou Feng, Yufen Xie, Zhenhui Zhu, Hui Guo, Guofeng Jin

“…However, existing remote sensing-based detection models often struggle with performance degradation in complex environments, as well as a trade-off between detection accuracy and real-time efficiency. …”
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Mixed image detection method of belt coal blockage and leakage based on improved RetinaNet mode by Qingjun Fu, Xiang Liu, Yinqiang Yan, Zhibin Guo

“…The test results show that this method can comprehensively collect the images of coal conveying by belt, and accurately identify the detection of coal blockage and coal leakage. This method is applied to the actual production environment, which can monitor the situation of belt coal transportation in real time and accurately detect coal blockage and leakage, which is of great significance to improve the production efficiency of coal transportation, reduce economic losses and ensure production safety.…”
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Detection Model for 5G Core PFCP DDoS Attacks Based on Sin-Cos-bIAVOA by Zheng Ma, Rui Zhang, Lang Gao

“…The development of 5G environments has several advantages, including accelerated data transfer speeds, reduced latency, and improved energy efficiency. Nevertheless, it also increases the risk of severe cybersecurity issues, including a complex and enlarged attack surface, privacy concerns, and security threats to 5G core network functions. …”
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Infrared Small Target Detection Based on Approximate Background Regularization and Bimodal Slice Based Graph Constraints by Xiaoling Ge, Zipeng Fu, Xuelian Yu, Weixian Qian, Kan Ren, Minjie Wan, Guohua Gu

“…Experimental results show that the proposed method outperforms state-of-the-art approaches in both detection performance and efficiency while demonstrating greater robustness in complex scenarios.…”
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gamUnet: designing global attention-based CNN architectures for enhanced oral cancer detection and segmentation by Jinyang Zhang, Hongxin Ding, Hongxin Ding, Runchuan Zhu, Weibin Liao, Weibin Liao, Junfeng Zhao, Junfeng Zhao, Min Gao, Xiaoyun Zhang

“…Additionally, we introduce an extended model, gamResNet, to further improve OSCC detection performance. Both architectures show significant improvements in handling the unique challenges of oral cancer images.ResultsExtensive experiments on public datasets show that our GAM-enhanced architecture significantly outperforms conventional models, achieving superior accuracy, robustness, and efficiency in OSCC diagnosis.DiscussionOur approach provides an effective tool for clinicians in diagnosing OSCC, reducing diagnostic variability, and ultimately contributing to improved patient care and treatment planning.…”
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Forced Oscillation Detection via a Hybrid Network of a Spiking Recurrent Neural Network and LSTM by Xiaomei Yang, Jinfei Wang, Xingrui Huang, Yang Wang, Xianyong Xiao

“…Deep learning (DL) holds significant potential for detecting forced oscillations correctly. However, existing artificial neural networks (ANNs) face challenges when employed in edge devices for timely detection due to their inherent complex computations and high power consumption. …”
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FDIA Attack Detection Technique for Smart Grids Based on Graph Reconstruction and Spatio-Temporal Joint Modeling by Gao Yuzhang, Xia Jing

“…With the widespread application of smart grids, the false data injection attack (FDIA) has become a major threat to power grid security. Traditional detection methods often have difficulty in effectively identifying such attacks, especially in complex environments. …”
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SDFSD-v1.0: A Sub-Meter SAR Dataset for Fine-Grained Ship Detection by Peixin Cai, Bingxin Liu, Peilin Wang, Peng Liu, Yu Yuan, Xinhao Li, Peng Chen, Ying Li

“…In the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship detection, with dataset quality as a crucial factor influencing detection accuracy. …”
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Enhanced YOLOv8-based method for space debris detection using cross-scale feature fusion by Yang Guo, Xianlong Yin, Yao Xiao, Zhengxu Zhao, Xu Yang, Chenggang Dai

“…The experimental results show that the detection accuracy and speed of the method are improved, and that they can meet the requirements of space debris detection in complex backgrounds.…”
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R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals by Kamirul Kamirul, Odysseas A. Pappas, Alin M. Achim

“…This unified design improves efficiency by eliminating redundant computation inherent in separate pooling. …”
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A comprehensive systematic review of intrusion detection systems: emerging techniques, challenges, and future research directions by Arjun Kumar Bose Arnob, Rajarshi Roy Chowdhury, Nusrat Alam Chaiti, Sudipta Saha, Ajoy Roy

“… The role of Intrusion Detection Systems (IDS) in the protection against the increasing variety of cybersecurity threats in complex environments, including the Internet of Things (IoT), cloud computing, and industrial networks. …”
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A Lightweight Remote-Sensing Image-Change Detection Algorithm Based on Asymmetric Convolution and Attention Coupling by Enze Zhang, Yan Li, Haifeng Lin, Min Xia

“…In recent years, breakthroughs in satellite sensor technology have generated vast volumes of data and complex scenes, presenting significant challenges for change-detection algorithms. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…The CBAM attention mechanism is added to the model to improve the extraction of subtle features of lesions in complex environments. Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. …”
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Rotation-Invariant Feature Enhancement with Dual-Aspect Loss for Arbitrary-Oriented Object Detection in Remote Sensing by Zhao Hu, Xiangfu Meng, Xinsong Liu, Zhuxiang Sun

“…Evaluated on the DIOR-R and HRSC2016 benchmarks, our method demonstrates robust detection capabilities for arbitrarily oriented objects, achieving competitive performance in both accuracy and efficiency. …”
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Defects Localization and Classification Method of Power Transmission Line Insulators Aerial Images Based on YOLOv5 EfficientNet and SVM by Lin Li, Qiaoling Yin, Xiaofeng Wang, Hang Wang

“…However, existing methods face challenges in achieving satisfactory accuracy, particularly in complex environments. Moreover, previous approaches primarily focus on detecting a single type of insulator defect without further categorizing them. …”
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Research on Blueberry Maturity Detection Based on Receptive Field Attention Convolution and Adaptive Spatial Feature Fusion by Bingqiang Huang, Zongyi Xie, Hanno Homann, Zhengshun Fei, Xinjian Xiang, Yongping Zheng, Guolong Zhang, Siqi Sun

“…Detecting small objects in complex outdoor conditions remains challenging. …”
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CUNet-CLSTM: A Novel Fusion of CUNet and CLSTM for Superior Liver Cancer Detection in CT Scans by K. Vijayaprabakaran, Padmanaban Ramalingam, Rajakumar Ramalingam, A. Ilavendhan, R. Vedhapriyavadhana

“…Despite the triumph of convolutional neural networks in medical image analysis, challenges such as overfitting, limited labeled data, and complex tumor morphology hinder accurate detection of liver cancer. …”
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Multiple Targets CFAR Detection Performance Based on an Intelligent Clustering Algorithm in K-Distribution Sea Clutter by Mansoor M. Al-dabaa, Eugen Laslo, Ahmed A. Emran, Ahmed Yahya, Ashraf Aboshosha

“…It is noteworthy that the proposed method achieves detection performance comparable to the more computationally intensive DBSCAN-CFAR while significantly reducing computational complexity. …”
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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

“…To tackle the challenge of wake waves from moving ships obscuring small targets, we introduce a gradient flow mechanism that improves detection efficiency under dynamic conditions. The Tail Wave Detection Method synergistically integrates gradient computation with target detection techniques. …”
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Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes by Karolina Buka, Zofia Parteka-Tojek, Abhishek Agarwal, Michał Denkiewicz, Sevastianos Korsak, Mateusz Chiliński, Krzysztof H. Banecki, Dariusz Plewczynski

“…Using comprehensive bioinformatic analysis, we show that a dual chromatin fixation method compared to the standard formaldehyde-only method, results in a substantially better signal-to-noise ratio, increased ChIP efficiency and improved detection of chromatin loops and architectural stripes. …”
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