YOLO-WAD for Small-Defect Detection Boost in Photovoltaic Modules by Yin Wang, Wang Yun, Gang Xie, Zhicheng Zhao

“…The experimental results show that YOLO-WAD detects our dataset with an overall accuracy of 95.6%, with the small-target defect detection accuracy reaching 86.3%, which is 4.1% and 9.5% higher than YOLOv10n and current mainstream models, verifying the feasibility of our algorithm.…”
Get full text

Transformer Online Monitoring Data Abnormal Value Detection and Cleaning by QIAN Yucheng, ZHEN Chao, JI Kun, ZHAO Changwei, FU Longming, ZHANG Yajing

“…The online monitoring data can monitor the status of the transformer in real time However, it is found that there is a problem of unreliable data, which is directly related to the accuracy of the subsequent status assessment In view of the characteristics of abnormal values in online monitoring data, and the general abnormal state detection method is based on the threshold, it is difficult to distinguish the noise data in time, so a method based on gray correlation and Kmeans clustering is proposed The gray correlation method is used to mine the degree of association of online multivariate time series data, and the strong correlation sequence is extracted to provide a basis for the subsequent multivariate sequence anomaly data detection. …”
Get full text

A Fast Image Segmentation Algorithm Based on Saliency Map and Neutrosophic Set Theory by Sensen Song, Zhenhong Jia, Jie Yang, Nikola K. Kasabov

Get full text

Synthesis of an Algorithm for Processing the Trajectories of Moving Objects Using the Methods of Data Clustering Theory by Nguyen Phung Bao, Quang Hieu Dang

“…For Information and Data Processing Centers (DPC) at control and management command posts, the issue of information mapping and forming the true trajectories of moving objects in the area of intersection of network detection zones is of particular importance. The use of conventional approaches to solving this problem involves issues  related to ensuring the efficient provision of users with complete and reliable information about trajectories in real time. …”
Get full text

Research on 3D Path Optimization for an Inspection Micro-Robot in Oil-Immersed Transformers Based on a Hybrid Algorithm by Junji Feng, Xinghua Liu, Hongxin Ji, Chun He, Liqing Liu

“…To address this challenge, we propose a hybrid algorithmic framework. First, the task of visiting inspection points is formulated as a Constrained Traveling Salesman Problem (CTSP) and solved using the Ant Colony Optimization (ACO) algorithm to generate an initial sequence of inspection nodes. …”
Get full text

Target Detection Label Assignment Method Based on Global Information by ZHANG Pei-pei, LU Zhen-yu

“…With the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved for overlapping, occlusion and other issues. …”
Get full text

Using Anomaly Detection to Search for Technosignatures in Breakthrough Listen Observations by Snir Pardo, Dovi Poznanski, Steve Croft, Andrew P. V. Siemion, Matthew Lebofsky

“…We implement a machine learning algorithm to search for extraterrestrial technosignatures in radio observations of several hundred nearby stars, obtained with the Parkes and Green Bank Telescopes by the Breakthrough Listen collaboration. …”
Get full text

Application of an improved pelican optimization algorithm based on comprehensive strategy in PV parameter identification by Xu Yong, Sang Bicong, Zhang Yi

“…Secondly, the position update formula of the Pelican optimization algorithm in the global detection phase is replaced by the position update formula of the red-tailed Eagle optimization algorithm in the soaring phase to obtain the adequacy of the Pelican optimization algorithm in solution space search. …”
Get full text

Detection of Fake Instagram Accounts via Machine Learning Techniques by Stefanos Chelas, George Routis, Ioanna Roussaki

“…This paper focuses on the detection of fake accounts on Instagram and proposes a novel solution that aims to address this problem. …”
Get full text

Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm by He Chuan, Qiu Dishan, Liu Jin

“…Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. …”
Get full text

An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation by Liang Xiang, Xiajie Zhao, Jianfeng Wang, Bin Wang

“…Thresholding image segmentation aims to divide an image into a number of regions with different feature attributes in order to facilitate the extraction of image features in the context of image detection and pattern recognition. However, existing threshold image-segmentation methods suffer from the problem of easily falling into locally optimal thresholds, resulting in poor image segmentation. …”
Get full text

Object detection and tracking in video sequences: formalization, metrics and results by R. P. Bohush, S. V. Ablameyko

Get full text

Coal mine conveyor monitoring video enhancement algorithm based on DP-YOLOv7 by Lei ZHANG

“…With the advancement of intelligent construction in coal mines, the intelligent technology level of belt conveyor as a key equipment of coal mine main transportation is increasing, and the application of video AI technology in the monitoring and inspecting system of coal mine belt conveyor has become a hot spot. Aiming at the problems encountered by video surveillance during the operation of belt conveyor, such as insufficient light, moisture and large coal dust pollution, a new DP-YOLOv7 video detection algorithm for coal mine belt conveyor is proposed based on YOLOv7 target detection algorithm. …”
Get full text

ECG Paper Digitization and R Peaks Detection Using FFT by Ibraheam Fathail, Vaishali D. Bhagile

“…It is employed to investigate particular varieties of aberrant heart activity, such as arrhythmias and conduction problems. One of the most essential tools for detecting heart problems is the electrocardiogram (ECG). …”
Get full text

Fast Processing of Massive Hyperspectral Image Anomaly Detection Based on Cloud-Edge Collaboration by Yunchang Wang, Jin Sun, Yang Xu, Zhihui Wei, Shangdong Zheng, Zebin Wu

“…With the improvement of hyperspectral image resolution, existing anomaly detection algorithms find it challenging to quickly process large volumes of hyperspectral data while fully exploiting spectral information. …”
Get full text

Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures by Luigi Coppolino, Salvatore D'Antonio, Valerio Formicola, Luigi Romano

“…In this work, we present a Fraud Detection System that classifies transactions in a Mobile Money Transfer infrastructure by using the data fusion algorithms derived from these new models. …”
Get full text

Early Detection of Parkinson's Disease: Ensemble Learning for Improved Diagnosis by Raut Komal, Balpande Vijaya

“…This paper proposed several machine learning algorithms such as Decision Tree, Random Forest, Logistic Regression and Support Vector Machine and design an ensemble of these models to detect and classify Parkinson's disease. …”
Get full text

A survey of streaming data anomaly detection in network security by Pengju Zhou

“…This article provides a comprehensive review and a multi-faceted analysis of recent algorithms for anomaly detection in network security. …”
Get full text

Detecting and Mitigating Wind Turbine Clutter for Airspace Radar Systems by Wen-Qin Wang

Get full text

Application of machine learning methods for automated detection of network intrusions by M. V. Babicheva, I. A. Tretyakov

“…It is shown that a machine learning-based network intrusion detection system can solve the problem of flexible protection that could adapt to the ever-changing nature of network attacks, since one of the most important advantages of machine learning in detecting network intrusions is the ability to learn the signs of attacks and identify cases that are uncharacteristic of those that were observed earlier.…”
Get full text