EBDet: Ellipse Feature Encode and Balanced Decoupling Label Assignment for Arbitrary-Oriented Ship Detection in Optical Remote Sensing Images by Tianqi Zhao, Yunhan Sun, Jin Qian, Zheng Li, Yunxiao Gao, Zhikang Zhao, Yongcheng Wang

“…To address these issues, a ship detector based on ellipse feature encoding (EFE) and balanced decoupling label assignment strategy (EBDet) is proposed, aiming to effectively integrate ship features during the crucial detection process. …”
Get full text

MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

“…To solve this problem, this paper proposes a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images. …”
Get full text

Research on Arc Fault Detection Based on Conditional Batch Normalization Convolutional Neural Network with Cost-Sensitive Multi-Feature Extraction by Xin Ning, Tianli Ding, Hongwei Zhu

“…Although existing studies have made progress in improving the accuracy of their detection, most methods have not proposed effective solutions that address the cost-sensitive problem of feature selection. …”
Get full text

Transforming Early Breast Cancer Detection: A Deep Learning Approach Using Convolutional Neural Networks and Advanced Classification Techniques by Arun Kumar Singh, Bireshwar Dass Mazumdar, Rohit Raja, Kamred Udham Singh, Ankit Kumar, Mohd Asif Shah

“…In a world where access to a doctor with specialised knowledge is limited, this study attempts to address the important limitations of current diagnostic strategies that facilitate the efficient detection of diseases. In the proposed method, we use transfer learning with a combination of classifiers, such as SVM, decision trees, and K-nearest neighbours, while implementing two different feature extraction approaches, PCA for dimensionality reduction and no PCA. …”
Get full text

An active learning driven deep spatio-textural acoustic feature ensemble assisted learning environment for violence detection in surveillance videos by Duba Sriveni, Dr.Loganathan R

“…In this paper, a novel and robust deep spatio-textural acoustic feature ensemble-assisted learning environment is proposed for violence detection in surveillance videos (DestaVNet). …”
Get full text

SARFA-Net: Shape-Aware Label Assignment and Refined Feature Alignment for Arbitrary-Oriented Object Detection in Remote Sensing Images by Yan Dong, Minghong Wei, Guangshuai Gao, Chunlei Li, Zhoufeng Liu

“…Arbitrary-oriented object detection in remote sensing images has witnessed significant progress in recent years. …”
Get full text

MLGFENet: Multiscale Local–Global Feature Enhancement Network for High-Resolution Remote Sensing Image Change Detection by Huanhuan Lv, Xianqi Yan, Hui Zhang, Cuiping Shi, Ruiqin Wang

“…The integration of a convolutional neural network (CNN) and a Transformer has become a dominant framework for change detection (CD) in remote sensing images, because of its ability to effectively model both local and global features. …”
Get full text

Inverse Gravimetric Problem Solving via Prolate Ellipsoidal Parameterization and Particle Swarm Optimization by Ruben Escudero González, Zulima Fernández Muñiz, Antonio Bernardo Sánchez, Juan Luis Fernández Martínez

Get full text

Adverse drug reaction signal detection via the long short-term memory model by Mengqi Cao, Yanna Chi, Jinyang Yu, Yu Yang, Ruogu Meng, Jinzhu Jia, Jinzhu Jia

“…The common detection methods have the problem of high false positive rate. …”
Get full text

Fusion of multi-scale and context for small target detection algorithm of unmanned aerial vehicle rescue by LIU Yuan, ZHAO Jing, JIANG Guoping, XU Fengyu, LU Ningyun

“…Aiming at the problem of insufficient feature information contained in small targets under unmanned aerial vehicle (UAV) images that led to insufficient detection accuracy of the model, a small target detection algorithm for UAV sea rescue images that integrated multi-scale and contextual information was proposed. …”
Get full text

Research on Improved YOLO11 for Detecting Small Targets in Sonar Images Based on Data Enhancement by Xiaochuan Wang, Zhiqiang Zhang, Xiaodong Shang

“…Existing sonar target detection methods suffer from low efficiency and accuracy due to sparse target features and significant noise interference in sonar images. …”
Get full text

Automatic detection of cognitive events using machine learning and understanding models’ interpretations of human cognition by Quang Dang, Murat Kucukosmanoglu, Michael Anoruo, Golshan Kargosha, Sarah Conklin, Justin Brooks

“…The problem is framed as a binary classification. We train one generalized model and four task-specific models on 1-s pupil diameter and gaze position segments. …”
Get full text

PFARN: Pyramid Fusion Attention and Refinement Network for Multiscale Ship Detection in SAR Images by Ke Li, Hang Yu, Suqi Li, Shanhu Chen, Bailu Wang

“…To address the aforementioned problems, this article proposes a novel detection algorithm named <italic>pyramid fusion attention and refinement network</italic> (PFARN) for SAR ship detection. …”
Get full text

Multipopulation Whale Optimization-Based Feature Selection Algorithm and Its Application in Human Fall Detection Using Inertial Measurement Unit Sensors by Haolin Cao, Bingshuo Yan, Lin Dong, Xianfeng Yuan

“…In addition, the proposed method is utilized to perform feature selection in human fall-detection tasks, and extensive real experimental results further illustrate the superior ability of the proposed method in addressing practical problems.…”
Get full text

WCANet: An Efficient and Lightweight Weight Coordinated Adaptive Detection Network for UAV Inspection of Transmission Line Accessories by Jiawei Chen, Pengfei Shi, Mengyao Xu, Yuanxue Xin, Xinnan Fan, Jinbo Zhang

“…To alleviate the above problems, we propose an innovative Weight Coordinated Adaptive Network (WCANet) in this paper, aiming to improve the efficiency and accuracy of high-voltage transmission accessories detection. …”
Get full text

Detection and identification of non-technical loss based on electricity consumption curve and deep learning by WANG Yunjing, XIAO Keyu, QU Zhengwei, HAN Xiaoming, DONG Haiyan, Popov Maxim Georgievitch

“…Finally, a multi-level neural network architecture is designed and deep learning is utilized to solve the multiclass classification problem of the feature sequences. Simulation based on actual power consumption dataset of a certain area shows that the research content can realize an effective detection of non-technical loss as well as identification of specific tampering strategies.…”
Get full text

Machine vision-based detection of key traits in shiitake mushroom caps by Jiuxiao Zhao, Jiuxiao Zhao, Wengang Zheng, Wengang Zheng, Yibo Wei, Yibo Wei, Qian Zhao, Qian Zhao, Jing Dong, Jing Dong, Xin Zhang, Xin Zhang, Mingfei Wang, Mingfei Wang

“…Secondly, the edge information detected by KL-Dexined was mapped onto the original image of shiitake mushroom caps, and using the OpenCV model,11 phenotypic key features including shiitake mushroom caps area, perimeter, and external rectangular length were obtained. …”
Get full text

Spammer group detection based on cascading and clustering of core figures by Qianqian Jiang, Chunrong Zhang, Ning Li, Dickson K. W. Chiu, Xianwen Fang, Shujuan Ji

“…Abstract The problem of collaborative spamming in e-commerce is gradually increasing, and traditional spammer group detection algorithms usually seem cumbersome and time-consuming when dealing with massive user review data. …”
Get full text

YOLOv8-UCB: Visual Detection of Pouch Battery Using Improved YOLOv8 by Hao Hao, Xiang Yu

“…Second, we constructed a distributed focal detection head CLLAHead, to better capture the features at different scales. …”
Get full text

Detection of Potentially Anomalous Cosmic Particle Tracks Acquired with CMOS Sensors: Validation of Rough k–Means Clustering with PCA Feature Extraction by Hachaj Tomasz, Piekarczyk Marcin, Wąs Jarosław

“…We apply a principal components analysis-based feature extraction method and rough k-means clustering for outlier detection. …”
Get full text