AI-Powered System for an Efficient and Effective Cyber Incidents Detection and Response in Cloud Environments by Mohammed Ashfaaq M. Farzaan, Mohamed Chahine Ghanem, Ayman El-Hajjar, Deepthi N. Ratnayake

“…The growing complexity and frequency of cyber threats in cloud environments call for innovative and automated solutions to maintain effective and efficient incident response. …”
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VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Additionally, a lightweight Optimized Shared Detection Head (OSDH-Head) is introduced, reducing computational complexity while improving detection efficiency. …”
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A low complexity detection algorithm for large scale multiuser MIMO based on message passing by Qiong WANG, Wei YE, Mingming JI

“…According to the problem of high complexity of base station detection in large scale multiuser multiple input multiple output (MIMO) system,a low complexity multiuser variable node full information Gaussian message passing iterative detection algorithm based on forced convergence (VFI-GMPID-FC) was proposed.Firstly,the traditional Gaussian message passing iterative detection (GMPID) algorithm was improved to obtain VFI-GMPID algorithm,the detection performance of the VFI-GMPID algorithm approximates the minimum mean square error detection (MMSE) algorithm,but the complexity was considerably less than the MMSE algorithm.Then,the VFI-GMPID-FC algorithm was proposed to reduce the complexity of the algorithm and improve the detection efficiency.Finally,the simulation results show that the proposed algorithm can effectively reduce the algorithm complexity while ensuring the detection performance.…”
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GSBYOLO: A lightweight Multi-Scale fusion network for road crack detection in complex environments by Yuhao Wang, Heran Zhu, Yirong Wang, Jianping Liu, Jun Xie, Bi Zhao, Siyue Zhao

“…However, existing detection methods face challenges such as varying target scales, large model parameters, and poor adaptability to complex backgrounds. …”
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YOLO-GML: An object edge enhancement detection model for UAV aerial images in complex environments. by Zhihao Zheng, Jianguang Zhao, Jingjing Fan

“…However, in practical application scenarios, there are many complex and highly uncertain factors, such as extreme weather changes, large scale and span of the target, complex background interference, motion ambiguity, etc., which makes accurate and real-time UAV target detection still a great challenge. …”
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Defect Detection and 3D Reconstruction of Complex Urban Underground Pipeline Scenes for Sewer Robots by Ruihao Liu, Zhongxi Shao, Qiang Sun, Zhenzhong Yu

“…Detecting defects in complex urban sewer scenes is crucial for urban underground structure health monitoring. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Method Building on two-year multi-angle wheat spike imagery, we propose an enhanced YOLOv9-LDS multi-scale object detection framework. The algorithm innovatively constructs a lightweight depthwise separable network (LDSNet) as backbone, balancing computational efficiency and accuracy through channel re-parameterization strategy; incorporates an Efficient Local Attention (ELA) module to build feature enhancement networks, and employs dual-path feature fusion mechanisms to strengthen edge texture responses, significantly improving discrimination of overlapping spikes and complex backgrounds. …”
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Balancing Complexity and Performance of Machine Learning Models for Avian Pests Sound Detection in Agricultural Environments by Micheline Kazeneza, Anna Sergeevna Bosman, Destiny Kwabla Amenyedzi, Damien Hanyurwimfura, Emmanuel Ndashimye, Anthony Vodacek

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Deep Learning-Based Efficient Model Development for Phishing Detection Using Random Forest and BLSTM Classifiers by Shan Wang, Sulaiman Khan, Chuyi Xu, Shah Nazir, Abdul Hafeez

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A Distributed Detection Method for Quality-related Faults in Complex Non-stationary Industrial Processes by Jie DONG, Daye LI, Yanmei WEI, Kaixiang PENG, Hui YANG

“…Therefore, this study proposes a new distributed quality-related fault detection method for complex non-stationary industrial processes based on dynamic and static feature fusion. …”
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A low-complexity AMP detection algorithm with deep neural network for massive mimo systems by Zufan Zhang, Yang Li, Xiaoqin Yan, Zonghua Ouyang

“…However, existing detection methods have not yet made a good tradeoff between Bit Error Rate (BER) and computational complexity, resulting in slow convergence or high complexity. …”
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Enhanced Yolov8 network with Extended Kalman Filter for wildlife detection and tracking in complex environments by Langkun Jiang, Li Wu

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A complex roadside object detection model based on multi-scale feature pyramid network by Zhihao Zheng, Jianguang Zhao, Jingjing Fan, Ruirui Bai, Jiana Zhao, Jianan Liu

“…Abstract In response to the challenges of false positives and misses caused by dense occlusions and small targets in complex road environments, this paper proposes an enhanced YOLOv8-based network named YOLO-RC for advanced road traffic object detection. …”
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IRSD-Net: An Adaptive Infrared Ship Detection Network for Small Targets in Complex Maritime Environments by Yitong Sun, Jie Lian

“…To address these issues, we propose an Infrared Ship Detection Network (IRSD-Net), a lightweight and efficient detection network built upon the YOLOv11n framework and specially designed for infrared maritime imagery. …”
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A Comparative Crash-Test of Manual and Semi-Automated Methods for Detecting Complex Submarine Morphologies by Vasiliki Lioupa, Panagiotis Karsiotis, Riccardo Arosio, Thomas Hasiotis, Andrew J. Wheeler

“…A large number of (more than 7000) small but prominent reefs were detected, which made manual mapping extremely time-consuming. …”
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<i>DSW-YOLO</i>-Based Green Pepper Detection Method Under Complex Environments by Yukuan Han, Gaifeng Ren, Jiarui Zhang, Yuxin Du, Guoqiang Bao, Lijun Cheng, Hongwen Yan

“…Experimental results show that on a custom green pepper dataset, <i>DSW-YOLO</i> outperformed the baseline by achieving gains of 2.9%, 2.7%, 2.2%, and 3.4% in P, R, mAP50, and mAP50-95, reducing parameters by 1.6 M, cutting inference time by 0.7 ms, and shrinking the model size to 5.31 MB. <i>DSW-YOLO</i> efficiently and accurately detects green peppers in complex field conditions, significantly improving detection accuracy while remaining lightweight, and provides theoretical and technical support for designing and optimizing pepper-picking robot vision systems.…”
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Hardware and Software Complex for the Study of the Joint Use of Technical Means Based on Various Physical Principles by E. I. Mikhnionok, A. V. Khizniak

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Mitigating Container Damage and Enhancing Operational Efficiency in Global Containerisation by Sergej Jakovlev, Tomas Eglynas, Mindaugas Jusis, Valdas Jankunas, Miroslav Voznak

“…To address these concerns, we present the Impact Detection Methodology (IDM), a system designed to monitor and detect impacts in real time, enhancing operational precision and safety. …”
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GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling by Xin Wang, Changchun Li, Chenyi Zhao, Yinghua Jiao, Hengmao Xiang, Xifang Wu, Huabin Chai

“…Additionally, the ASF-Gather and Distribute (ASF-GD) module optimizes the feature extraction component of the original YOLOv7 network, improving the model’s robustness and accuracy in complex scenarios. Ablation experiments validate the effectiveness of the proposed methods.Compared with classic models such as Faster R-CNN, YOLOv5, YOLOv7, and YOLOv8, the GrainNet model achieves better detection performance and computational efficiency in various scenarios and adhesion levels. …”
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YOLO-GL for efficient multi-target detection in large FOV via hierarchical feature fusion by Xinyu Chen, Chengjun Dong, Tong Cui, Guangming Lv, Yan Ren

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