Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…The practical significance of the proposed trajectory features and the possibility of their implementation in the development of an algorithm for recognizing low-flying low-speed radar targets using passive coherent radar systems was established. …”
Get full text

Fault detection in electrical power systems using attention-GRU-based fault classifier (AGFC-Net) by Deepen Khandelwal, Prateek Anand, Mayukh Ray, Sangeetha R. G.

“…Experimental results show that AGFC-Net attains a fault detection accuracy of 99.52%, better than conventional machine learning and deep learning algorithms. …”
Get full text

Tree-Related High-Impedance Fault in Distribution Systems: Modeling, Detection, and Ignition Risk Assessment (Review) by Chunlan Yang, Wenhai Zhang, Rui Tang, Xianyong Xiao

“…In modeling, there is a lack of frameworks that simultaneously elucidate underlying mechanisms and support detection algorithms. In detection algorithms, the existing methods have not been adequately validated under complex environmental conditions. …”
Get full text

Intrusion Detection Using Machine Learning for Risk Mitigation in IoT-Enabled Smart Irrigation in Smart Farming by Abhishek Raghuvanshi, Umesh Kumar Singh, Guna Sekhar Sajja, Harikumar Pallathadka, Evans Asenso, Mustafa Kamal, Abha Singh, Khongdet Phasinam

“…In the preprocessing of the NSL-KDD data set, first all symbolic features are converted to numeric features. Feature extraction is performed using principal component analysis. …”
Get full text

Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…Experimental results demonstrate the algorithm’s superior performance in UAV remote sensing applications such as crop disease monitoring and traffic congestion detection, offering an efficient solution for real-time edge-device deployment.…”
Get full text

A Novel Method for Water Surface Debris Detection Based on YOLOV8 with Polarization Interference Suppression by Yi Chen, Honghui Lin, Lin Xiao, Maolin Zhang, Pingjun Zhang

“…These optical artifacts severely impair the performance of conventional detection algorithms, increasing both false positives and missed detections. …”
Get full text

SB‐YOLO‐V8: A Multilayered Deep Learning Approach for Real‐Time Human Detection by Prince Alvin Kwabena Ansah, Justice Kwame Appati, Ebenezer Owusu, Edward Kwadwo Boahen, Prince Boakye‐Sekyerehene, Abdullai Dwumfour

“…For instance, real‐time detection and detection of humans in agricultural settings pose challenges that demand sophisticated vision algorithms. …”
Get full text

Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Abstract To resolve the drawbacks of slow speed, excessive parameters, and high computational demands associated with deep learning-based conveyor belt foreign object detection methods, a lightweight algorithm for detecting foreign objects on conveyors based on an improved Yolov8n model is proposed. …”
Get full text

Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Finally, the crayfish optimization algorithm (COA) adjusts the VAE model’s hyperparameter values, improving classification. …”
Get full text

Internet of Things Assisted Plant Disease Detection and Crop Management Using Deep Learning for Sustainable Agriculture by Eman A. Al-Shahari, Ghadah Aldehim, Mohammed Aljebreen, Jehad Saad Alqurni, Ahmed S. Salama, Sitelbanat Abdelbagi

“…The integration of Internet of Things (IoT) technology with deep learning (DL) algorithms has revolutionized plant disease detection and crop management and paved the way for sustainable agricultural practices. …”
Get full text

DAFDM: A Discerning Deep Learning Model for Active Fire Detection Based on Landsat-8 Imagery by Xu Gao, Wenzhong Shi, Min Zhang, Lukang Wang

“…Traditional methods for detecting AFs rely on the statistical analysis of AF radiance and background features. …”
Get full text

An Enhanced Shuffle Attention with Context Decoupling Head with Wise IoU Loss for SAR Ship Detection by Yunshan Tang, Yue Zhang, Jiarong Xiao, Yue Cao, Zhongjun Yu

“…Recent deep learning advancements have led to improved ship detection algorithms, enhancing accuracy and speed over traditional Constant False-Alarm Rate (CFAR) methods. …”
Get full text

SDMSEAF-YOLOv8: a framework to significantly improve the detection performance of unmanned aerial vehicle images by Linxuan Li, Xiaoyu Liu, Xuan Chen, Fengjuan Yin, Bin Chen, Yufeng Wang, Fanbin Meng

“…The detailed, high-resolution images captured by drones pose challenges to target detection algorithms with complex scenes and small-sized targets. …”
Get full text

A Metric Learning-Based Improved Oriented R-CNN for Wildfire Detection in Power Transmission Corridors by Xiaole Wang, Bo Wang, Peng Luo, Leixiong Wang, Yurou Wu

“…Compared with other commonly used object detection algorithms, the model developed in this study exhibited improved detection performance on the test dataset, offering research support for wildfire monitoring in power transmission corridors.…”
Get full text

Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…This method combines advanced signal processing techniques and deep learning algorithms to provide a practical solution for motor broken rotor bar detection.…”
Get full text

A 2D linear canonical transform partition algorithm(二维线性正则变换剖分算法) by 赵伟康(ZHAO Weikang), 侯建伟(HOU Jianwei), 刘晴晴(LIU Qingqing)

“…To enhance the computation speed of linear canonical transform image representation, in this paper, an effective image representation algorithm is proposed by using linear canonical transform series combined with a non-uniform partition algorithm. …”
Get full text

Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm by Ghada Moh. Samir Elhessewi, Mohammed Yahya Alzahrani, Mohammad Alamgeer, Abdulbasit A. Darem, Da’ad Albalawneh, Mohammed Alqahtani, Mutasim Al Sadig, Sultan Alanazi

Get full text

Enhancing diabetic retinopathy detection through federated convolutional neural networks: Exploring different stages of progression by Saad Alanazi, Rayan Alanazi

“…The combination of SMOTE technology data pre-processing, filtering approaches, VGG-based segmentation, federated learning, and CNN (FedCNN) categorization produces encouraging results, demonstrating the feasibility of scalable and secure DR detection systems. The VGG was created primarily for feature extraction and is well-known for its ability to gather fine visual details. …”
Get full text

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

“…This study evaluates the existing state-of-the-art IDS methodologies using Deep Learning (DL) approaches, and advanced feature engineering techniques. This research also highlights the success of models such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Explainable AI (XAI) in improving detection accuracy as well as computational efficiency and interoperability. …”
Get full text

The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning. by Bo Yu, Zheng Wang, Shangke Liu, Xiaomin Liu, Ruixin Gou

“…When the number of iTree n is determined to be 100, and the corresponding number of samples w is determined to be 10, the algorithm has the best detection effect. The FDIAs detection algorithm model based on CNN-GRU shows good detection effects under high attack intensity, with an accuracy rate of more than 95%, and its performance is better than other traditional detection algorithms. …”
Get full text