Visual Detection on Aircraft Wing Icing Process Using a Lightweight Deep Learning Model by Yang Yan, Chao Tang, Jirong Huang, Zhixiong Cen, Zonghong Xie

“…High transparency and blurred edges of icing areas in wing images pose challenges to wing icing detection by machine vision. To address these challenges, this study proposes a detection model, Wing Icing Detection DeeplabV3+ (WID-DeeplabV3+), for efficient and precise aircraft wing leading edge icing detection under natural lighting conditions. …”
Get full text

A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…Additionally, Machine Learning (ML) approaches show significant promise for detecting intrusions in IoT environments. However, the high dimensionality, class imbalance, and complexity of network traffic—combined with the dynamic nature of sensor networks—pose substantial challenges to the development of efficient and effective detection algorithms. …”
Get full text

Adapting Vision Transformer-Based Object Detection Model for Handwritten Text Line Segmentation Task by Osman Furkan KARAKUŞ, Ayla GULCU, Ali Can KARACA

“…We benefit from DETR model with a ResNet-101 backbone pretrained on the Common Objects in Context (COCO) object detection training dataset, and re-train this model using our novel, complex line segmentation dataset consisting of 1,610 handwritten forms. …”
Get full text

Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications by Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong

“…Together, the other two algorithms failed to detect. The findings highlight the RANSAC-CyF algorithm’s superior accuracy, robustness, and adaptability in complex forest environments, significantly improving the efficiency and precision of individual tree trunk detection for forestry surveys and ecological research.…”
Get full text

LArcNet: Lightweight Neural Network for Real-Time Series AC Arc Fault Detection by Kamal Chandra Paul, Chen Chen, Yao Wang, Tiefu Zhao

“…Detecting series ac arc faults in diverse residential loads is challenging due to variations in load characteristics and noise. …”
Get full text

Enhanced Cloud Detection Using a Unified Multimodal Data Fusion Approach in Remote Images by Yan Mo, Puhui Chen, Wanting Zhou, Wei Chen

“…Aiming at the complexity of network architecture design and the low computational efficiency caused by variations in the number of modalities in multimodal cloud detection tasks, this paper proposes an efficient and unified multimodal cloud detection model, M2Cloud, which can process any number of modal data. …”
Get full text

Exploiting question-answer framework with multi-GRU to detect adverse drug reaction on social media by Jiao-huang Luo, Ai-hua Yang

“…Therefore, the post-marketing detection of ADRs in a timely and accurate manner becomes imperative. …”
Get full text

EER-DETR: An Improved Method for Detecting Defects on the Surface of Solar Panels Based on RT-DETR by Jiajun Dun, Hai Yang, Shixin Yuan, Ying Tang

“…In the context of the rapid popularization of clean energy, the precise identification of surface defects on photovoltaic modules has become a core technical bottleneck limiting the operational efficiency of power stations. In response to the shortcomings of existing detection methods in identifying tiny defects and model efficiency, this study innovatively constructed the EER-DETR detection framework: firstly, a feature reconstruction module WDBB with a differentiable branch structure was introduced to significantly enhance the feature retention ability for fine cracks and other small targets; secondly, an adaptive feature pyramid network EHFPN was innovatively designed, which achieved efficient integration of multi-level features through a dynamic weight allocation mechanism, reducing the model complexity by 9.7% while maintaining detection accuracy, solving the industry problem of “precision—efficiency imbalance” in traditional feature pyramid networks; finally, an enhanced upsampling component was introduced to effectively address the problem of detail loss that occurs in traditional methods during image resolution enhancement. …”
Get full text

A software reliability model for open source big data system considering fault introduction and fault removal efficiency by Jinyong Wang, Haijun Geng, Pengda Li

“…In this paper, we focus on the characteristics of open source big data system software development and testing, such as the complexity of fault detection, the possibility of introducing new faults and fault removal efficiency factors during fault debugging, to establish a new software reliability model. …”
Get full text

A method for detecting abnormal electricity prices at charging stations based on two rounds of clustering by XUE Xiaohui, ZHANG Wen, ZHANG Jing, CHEN Yan, ZHOU Chun, CHEN Liang, CAO Zengwei

“…Due to the complexity of electricity pricing policies, multiple implementation steps, and difficulty in regulation, errors in electricity pricing implementation occur from time to time. …”
Get full text

Fast link-establishment method of integrated of communication and detection based on short-wave digital channelization by Guojun LI, Cuiling XIANG, Changrong YE, Zunli WANG

“…A link-establishment method based on short-wave digital channelized receiver was proposed for the traditional automatic link establishment technology in short-wave communications with the low accuracy of frequency selection, low efficiency of link establishment, and low utilization of resources, etc.The parallel receiving mechanism for full frequency band in short-wave communications was realized by using digital channelization.An integrated waveform of communication and detection was designed to deal with the time redundancy and equipment compatibility problems caused by waveform switching during link establishment.A fast link-establishment method was designed, to achieve a fast and robust connection in complex electromagnetic environments.The results show that the channelized structure can enhance the receiving performance of the link-establishment system, the link-establishment method has obvious advantages, channel parameter estimation method has a high estimation accuracy compared to the traditional link-establishment method and the applicability of the proposed method in practical short-wave channel environment is verified.…”
Get full text

Fast link-establishment method of integrated of communication and detection based on short-wave digital channelization by Guojun LI, Cuiling XIANG, Changrong YE, Zunli WANG

“…A link-establishment method based on short-wave digital channelized receiver was proposed for the traditional automatic link establishment technology in short-wave communications with the low accuracy of frequency selection, low efficiency of link establishment, and low utilization of resources, etc.The parallel receiving mechanism for full frequency band in short-wave communications was realized by using digital channelization.An integrated waveform of communication and detection was designed to deal with the time redundancy and equipment compatibility problems caused by waveform switching during link establishment.A fast link-establishment method was designed, to achieve a fast and robust connection in complex electromagnetic environments.The results show that the channelized structure can enhance the receiving performance of the link-establishment system, the link-establishment method has obvious advantages, channel parameter estimation method has a high estimation accuracy compared to the traditional link-establishment method and the applicability of the proposed method in practical short-wave channel environment is verified.…”
Get full text

PNet-IDS: A Lightweight and Generalizable Convolutional Neural Network for Intrusion Detection in Internet of Things by Auwal Sani Iliyasu, Abdul Jabbar Siddiqui, Houbing Song, Fahad Jibrin Abdu

“…To address this pressing issue, we propose PNet-IDS, a novel lightweight convolutional neural network (CNN)-based method to reduce computational complexity and optimize on-device resource usage for real-time intrusion detection. …”
Get full text

An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network by Yanbin Weng, Meng Xu, Xiahu Chen, Cheng Peng, Hui Xiang, Peixin Xie, Hua Yin

Get full text

RT-DETR-Pro: An Enhanced RT-DETR Model for Visual Detection of Photovoltaic Module Defects by Yunliang Chen, Mingtao Shan, Wei Zhou, Bing Ma, Xun Mei

“…An enhanced RT-DETR (Real-Time Detection Transformer) model, RT-DETR-Pro, is proposed to address the problem of low recognition rates for visual detection of PV (photovoltaic) module defects by traditional object detection methods. …”
Get full text

A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…The proposed model exhibits significant advantages in terms of lightweight design and improved detection efficiency, demonstrating substantial potential for practical deployment. …”
Get full text

K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

“… Phishing detection is considered a critical problem in cybersecurity, and utilising machine learning with an efficient feature selection method for precisely identifying malicious websites is deemed the most critical challenge. …”
Get full text

TW-YOLO: An Innovative Blood Cell Detection Model Based on Multi-Scale Feature Fusion by Dingming Zhang, Yangcheng Bu, Qiaohong Chen, Shengbo Cai, Yichi Zhang

“…However, due to the diversity and complexity of blood cell images, traditional models still exhibit deficiencies in blood cell detection. …”
Get full text

A Novel Approach to Android Malware Intrusion Detection Using Zero-Shot Learning GANs by Syed Atir Raza Shirazi, Mehwish Shaikh

“…The results of this study demonstrate the potential of this method for improving the accuracy and efficiency of intrusion detection systems in real-world scenarios. …”
Get full text

Arbitrarily Oriented Object Detection in Remote Sensing Images Based on Improved YOLOv4-CSP by Ziyang Zheng, Ting Zhang, Zhaoying Liu, Bo Liu, Yujian Li, Changming Sun

“…In order to further improve the detection accuracy and provide a more efficient model for scenes that require real-time detection, we propose an improved YOLOv4-CSP network for rotating object detection in remote sensing images. …”
Get full text