Detection of hydrophobicity grade of insulators based on AHC-YOLO algorithm by Shaotong Pei, Weiqi Wang, Peng Wu, Chenlong Hu, Haichao Sun, Keyu Li, Mianxiao Wu, Bo Lan

“…To address this issue, this paper proposes a YOLO algorithm for the precise detection of composite insulator hydrophobicity. The algorithm integrates a high-performance GPU network (HGNetv2), a mixed local channel attention mechanism (MLCA), lightweight convolution (CSPPC), and the Inner-WIoU loss function, significantly reducing the network’s burden and improving the accuracy of recognizing composite insulator sheds and classifying their hydrophobicity levels. …”
Get full text

Pavement crack detection method based on improved YOLOv5 by Wang Xiangqian, Cheng Gaoli, Hu Peng, Xia Xiaohua

“…Firstly, the MobileNetv3 network is used instead of the YOLOv5 backbone network to reduce the model size. Secondly, the C3TR and CBAM modules are introduced to improve the network characterization ability, and the loss function is replaced with EIOU to improve the robustness of the model. …”
Get full text

Anomaly Detection Approach Based on Deep Neural Network and Dropout by Zaid Hussien et al.

“…In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. …”
Get full text

DCW-YOLO: Road Object Detection Algorithms for Autonomous Driving by Hongge Ren, Fangke Jing, Song Li

“…Finally, the deleterious gradients generated by low-quality examples are reduced using the Wise-IoU v3 bounding box loss function in conjunction with a dynamic non-monotonic focusing mechanism utilizing an anchor box gradient gain assignment strategy. …”
Get full text

Detection of egg appreance based on Fasternet and YOLOv5 model by WEI Jingxin, CHEN Zhongju, XU Haoran

“…The Bottleneck module in the C3 structure was replaced by the Fasternet Block module to reduce the parameters and improve the percision in the process of detection. …”
Get full text

Presepsin in Hepatic Pathology: Bridging the Gap in Early Sepsis Detection by Dana-Maria Bilous, Mihai Ciocîrlan, Cătălina Vlăduț, Carmen-Georgeta Fierbințeanu-Braticevici

“…Traditional biomarkers such as C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) often have reduced diagnostic reliability in this subgroup, due to impaired liver and renal function. …”
Get full text

LUNG FUNCTION AND RESPIRATORY MUSCLE STRENGTH IN OBESE IN CHILDREN by E. G. Furman, A. M. Yarulina, L. V. Sofronova

“…Children with obesity need to monitor the lung function and evaluate the strength of the respiratory muscles for early detection of functional disorders of the respiratory system.…”
Get full text

A Lightweight Barcode Detection Algorithm Based on Deep Learning by Jingchao Chen, Ning Dai, Xudong Hu, Yanhong Yuan

“…Finally, the reconstruction of the model’s detection head and the modification of the loss function are implemented to enhance the model’s training quality and reduce the model’s error in barcode detection. …”
Get full text

An Artificial Intelligence QRS Detection Algorithm for Wearable Electrocardiogram Devices by Zihao Li, Wenliang Zhu, Yiheng Xu, Yunbo Guo, Junbo Li, Peng Song, Ying Liang, Binquan You, Lirong Wang

“…Significance: Our method canceled the repeated deployment of the QRS detection function to different lead configurations in the electrocardiogram (ECG) diagnostic system. …”
Get full text

Detection of Electric Network Frequency in Audio Using Multi-HCNet by Yujin Li, Tianliang Lu, Shufan Peng, Chunhao He, Kai Zhao, Gang Yang, Yan Chen

“…With the increasing application of electrical network frequency (ENF) in forensic audio and video analysis, ENF signal detection has emerged as a critical technology. However, high-pass filtering operations commonly employed in modern communication scenarios, while effectively removing infrasound to enhance communication quality at reduced costs, result in a substantial loss of fundamental frequency information, thereby degrading the performance of existing detection methods. …”
Get full text

Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

“…Moreover, the parameter count and GFLOPs are reduced by 26.6% and 22.2%, respectively. Thus, the proposed model effectively balances detection performance and lightweight design, making it well-suited for real-time applications on resource-constrained computing devices.…”
Get full text

A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…Introduce SIoU instead of the original loss function to accelerate model convergence. Finally, the introduction of the Ghost module to optimize the backbone network can reduce the computational and parametric quantities of the model without losing the model performance, improve the detection speed, and make the model easier to be deployed on resource-constrained devices. …”
Get full text

YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

“…At last, the MPDIoU loss function was employed, resulting in improved bounding box detection accuracy and accelerated model convergence. …”
Get full text

Research on intrusion detection model based on synchronization of heterogenous executer by YU Hong, ZHU Zhengbin, WEI Shuai, GUO Wei, LAN Julong

“…Additionally, synchronization of the target functions of heterogeneous executers was achieved through internal and external event conversions, thereby reducing the false positive rate caused by the heterogeneity of executers. …”
Get full text

Impact of carbohydrate-reduced nutrition in septic patients on ICU: study protocol for a prospective randomised controlled trial by Tim Rahmel, Michael Adamzik, Max Hübner, Björn Koos, Alexander Wolf, Katrin-Maria Willemsen, Gabriele Strauß, David Effinger, Simone Kreth

“…The primary endpoint is the detection of ketone bodies in patients’ blood and urine samples. …”
Get full text

An insulator target detection algorithm based on improved YOLOv5 by Bing Zeng, Zhihao Zhou, Yu Zhou, Dilin He, Zhanpeng Liao, Zihan Jin, Yulu Zhou, Kexin Yi, Yunmin Xie, Wenhua Zhang

“…Abstract Drone inspections are widely utilized in the detection of insulators in power lines. To address issues with traditional object detection algorithms, such as large parameter counts, low detection accuracy, and high miss rates, this paper proposes an insulator detection algorithm based on an improved YOLOv5 model. …”
Get full text

DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

“…Improved attention, loss function, and suppression enhance detection accuracy, while lightweight C3 module reduces computation time. …”
Get full text

Detection of Maize Pathogenic Fungal Spores Based on Deep Learning by Yijie Ren, Ying Xu, Huilin Tian, Qian Zhang, Mingxiu Yang, Rongsheng Zhu, Dawei Xin, Qingshan Chen, Qiaorong Wei, Shuang Song

“…Timely detection of pathogen spores is fundamental to ensuring early intervention and reducing the spread of corn diseases, like northern corn leaf blight, corn head smut, and corn rust. …”
Get full text

STED nanoscopy with time-gated detection: theoretical and experimental aspects. by Giuseppe Vicidomini, Andreas Schönle, Haisen Ta, Kyu Young Han, Gael Moneron, Christian Eggeling, Stefan W Hell

“…We present a theoretical framework and experimental data that characterize the time evolution of the effective point-spread-function of a STED microscope and illustrate the physical basis, the benefits, and the limitations of time-gated detection both for CW and pulsed STED lasers. …”
Get full text

A Lightweight AI-Based Approach for Drone Jamming Detection by Sergio Cibecchini, Francesco Chiti, Laura Pierucci

“…However, drone networks are particularly vulnerable to jamming attacks, a type of availability attack that can disrupt network operation and hinder drone functionality. In this paper, we propose a low complexity unsupervised machine learning approach for the detection of constant and periodic jamming attacks, using the Isolation Forest algorithm. …”
Get full text