Combining 2D texture and 3D geometry features for Reliable iris presentation attack detection using light field focal stack by Zhengquan Luo, Yunlong Wang, Nianfeng Liu, Zilei Wang

“…Abstract Iris presentation attack detection (PAD) is still an unsolved problem mainly due to the various spoof attack strategies and poor generalisation on unseen attackers. …”
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MFFNet: a building change detection method based on fusion of spectral and geometric information by Zhihao Guo, Jianping Pan, Peng Xie, Ling Zhu, Chen Qi, Xunxun Wang, Yihan Yang, Yan Wang, Huijuan Zhang, Zhaohui Ren

“…However, when using remote sensing images, shadows, vegetation and objects with similar spectral and morphological characteristics as buildings can cause false detections, omissions and incomplete patch edges. To address this issue, we develop the multiscale feature fusion network for dual-modal data (MFFNet), which has two main aspects: (1) The multi-dual-modal feature fusion module detects changes in features with similar spectral and morphological characteristics as buildings. …”
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Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox by Samuel M. Gbashi, Paul A. Adedeji, Obafemi O. Olatunji, Nkosinathi Madushele

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FD-IDS: Federated Learning with Knowledge Distillation for Intrusion Detection in Non-IID IoT Environments by Haonan Peng, Chunming Wu, Yanfeng Xiao

“…Together, these mechanisms effectively alleviate the problem of model drift. Experiments conducted on both the Edge-IIoT and N-BaIoT datasets demonstrate that FD-IDS achieves promising detection performance across multiple evaluation metrics.…”
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Technologies and Algorithms for Building the Augmented Reality by I. A. Blagoveshchenskiy, N. A. Demyankov

“…The authors give a short description and the main characteristics only of two of them: genetic algorithms and feature detection & description. For a programmatic implementation of those algorithms one can use special libraries like OpenCV and AForge.NET, also mentioned in the article. …”
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Problems in the formation and implementation of the methodology for investigating homicides related to domestic violence by R. L. Stepaniuk, V. O. Husieva, V. V. Kikinchuk

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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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A hybrid attack detection strategy for cybersecurity using moth elephant herding optimisation‐based stacked autoencoder by Abdullah Shawan Alotaibi

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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. …”
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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. …”
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SODRS: Semisupervised Learning for One-Stage Small Object Detection in Remote Sensing Images by Mingquan Liu, Lei Kuang, Chengjun Li, Jing Tian, Zifang Chen, Xuewu Han

“…Small object detection in remote sensing images faces challenges such as weak features, vulnerability to interference, and limited object visibility. …”
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A Local Discrete Feature Histogram for Point Cloud Feature Representation by Linjing Jia, Cong Li, Guan Xi, Xuelian Liu, Da Xie, Chunyang Wang

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GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…The problem of inadequate object detection accuracy in complex remote sensing scenarios has been identified as a primary concern. …”
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Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation by Jungpil Shin, Abu Saleh Musa Miah, Rei Egawa, Koki Hirooka, Md. Al Mehedi Hasan, Yoichi Tomioka, Yong Seok Hwang

“…In response to these challenges, this paper proposes a novel three-stream spatio-temporal feature-based human fall detection system. Our system incorporates joint skeleton-based spatial and temporal Graph Convolutional Network (GCN) features, joint motion-based spatial and temporal GCN features, and residual connections-based features. …”
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The Je Sais Tout Magazine and the Features of Belle Epoque Mass Reading (A New Book by Daniel Couégnas) by Kirill A. Chekalov

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