TSMGA: Temporal-Spatial Multiscale Graph Attention Network for Remote Sensing Change Detection by Xiaoyang Zhang, Genji Yuan, Zhen Hua, Jinjiang Li

“…In the field of remote sensing change detection, accurately capturing temporal change information and efficiently integrating multilevel information is a major challenge. …”
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Research on the Rapid Detection of Formaldehyde Emission From Wood-Based Panels Based on the AMSHKELM by Yinuo Wang, Huanqi Zheng, Hua Wang, Yucheng Zhou

“…This model utilizes sensor data, which provides ease of use and rapid detection, as input and formaldehyde emission data measured by the full-scale chamber method as output. …”
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Phylogenetic Diversity and Quantitative PCR Detection of <i>Erwinia amylovora</i> in Xinjiang, China by Nuoya Fei, Bo Song, Jianpei Yan, Haoyu Wei, Tingchang Zhao, Wei Guan, Weiqin Ji, Yuwen Yang

“…A quantitative PCR detection system based on the <i>trp</i> gene sequence was developed and optimized. …”
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Research on Detection and Counting Method of Green Walnut Based on YOLOv8n-RBP by Bangbang Chen, Keke Tan, Kun Li, Baojian Ma, Xiangdong Liu

“…Second, a BiFPN-GLSA module is introduced to replace the Path Aggregation Network (PANet) in the neck, improving the fusion of feature layers from the backbone and Neck networks and enhancing the model&#x2019;s ability to capture both global and local spatial features. Lastly, to address the weak generalization and slow convergence issues of the CIoU loss function in detection tasks, the PIoUv2 loss function is employed to accelerate bounding box regression and improve detection performance. …”
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MSOAR-YOLOv10: Multi-Scale Occluded Apple Detection for Enhanced Harvest Robotics by Heng Fu, Zhengwei Guo, Qingchun Feng, Feng Xie, Yijing Zuo, Tao Li

“…The accuracy of apple fruit recognition in orchard environments is significantly affected by factors such as occlusion and lighting variations, leading to issues such as missed and false detections. To address these challenges, particularly related to occluded apples, this study proposes an improved apple-detection model, MSOAR-YOLOv10, based on YOLOv10. …”
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High-Precision Stored-Grain Insect Pest Detection Method Based on PDA-YOLO by Fuyan Sun, Zhizhong Guan, Zongwang Lyu, Shanshan Liu

“…To address these limitations, we proposed PDA-YOLO, an improved stored-grain insect pest detection algorithm based on YOLO11n which integrates three key modules: PoolFormer_C3k2 (PF_C3k2) for efficient local feature extraction, Attention-based Intra-Scale Feature Interaction (AIFI) for enhanced global context awareness, and Dynamic Multi-scale Aware Edge (DMAE) for precise boundary detection of small targets. …”
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MTFSR: Multitemporal and Spatial Feature Reconstruction Denoising Network for Remote Sensing Change Detection by YeKai Cui, Peng Duan, Jinjiang Li

“…With the widespread application of convolutional neural networks (CNNs) in remote sensing (RS) technologies, change detection (CD) has attracted increasing attention in environmental monitoring research. …”
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Multi-Scenario Remote Sensing Image Forgery Detection Based on Transformer and Model Fusion by Jinmiao Zhao, Zelin Shi, Chuang Yu, Yunpeng Liu

“…Recently, remote sensing image forgery detection has received widespread attention. To improve the detection accuracy, we build a novel scheme based on Transformer and model fusion. …”
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Fault detection algorithm for underground conveyor belt deviation based on improved RT-DETR by AN Longhui, WANG Manli, ZHANG Changsen

“…Current research on conveyor belt deviation detection mainly focuses on extracting the straight-line features of belt edges. …”
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Semantic enhancement and change consistency network for semantic change detection in remote sensing images by Zhenghao Jiang, Biao Wang, Peng Zhang, Yanlan Wu, Zhiyuan Ye, Hui Yang

“…Semantic Change Detection (SCD) identifies binary change information and determines the ‘from-to’ types, revealing not only ‘where’ changes occurred but also ‘what’ the changes are. …”
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Neural Networks Detection of Low-Amplitude Components on ECG Using Modified Wavelet Transform by A. V. Mnevets, N. G. Ivanushkina

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Detection of Sedimentary Basins and Karstic Faults in the Yucatán Peninsula by Gravity Inversion and Euler Deconvolution by José Carlos Ortiz-Alemán, Mauricio Nava-Flores, Jaime Humberto Urrutia-Fucugauchi, Sebastián Ortiz-Aguilar, Mauricio Gabriel Orozco-del-Castillo, Sebastian López-Juárez

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Post-Hoc Categorization Based on Explainable AI and Reinforcement Learning for Improved Intrusion Detection by Xavier Larriva-Novo, Luis Pérez Miguel, Victor A. Villagra, Manuel Álvarez-Campana, Carmen Sanchez-Zas, Óscar Jover

“…The massive usage of Internet services nowadays has led to a drastic increase in cyberattacks, including sophisticated techniques, so that Intrusion Detection Systems (IDSs) need to use AP technologies to enhance their effectiveness. …”
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Detection and Quantification of Aflatoxins from Commercial Poultry Feed in the Federal Capital Territory, Nigeria by Bridget Maria Jessica Adah, Samuel Mailafia, H O K Olabode, Monday Onapka, James Agbo Ameh, Martha Echioda Ogbole, Odey Odey Ebenezer, Ifeanyi Cajetan Casmir

“… Study’s Excerpt: • Aflatoxins B1 and B2 were detected in commercial poultry feeds in FCT, Nigeria…”
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Federated Learning for Fall Detection With Multimodal Residual Fusion and Pareto-Optimized Client Selection by Bao-Quan Wang, Fan Yang, Yi Wang, Fan Zhao, Yun-Fei Han, Yu-Peng Ma

“…With the increasing aging population and the prevalence of chronic diseases, fall detection has become a critical component in elderly healthcare monitoring. …”
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A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…First, image standardization, including size normalization and background removal, is applied to produce standard images; then, the modified dynamic histogram equalization is implemented to enhance the low-contrast standard brain images, and skull removal based on outlier detection is presented. Furthermore, hybrid features, including gray-level co-occurrence matrix, pyramid histogram of the oriented gradient, modified completed local binary pattern, and intensity-based features are extracted together from the enhanced images, and their dimensions are reduced by principal component analysis. …”
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Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

“…At the same time, a P2 small target detection layer is added on the basis of the original three output layers of YOLOv5s, which increases the multi-scale receptive field of the model and can capture global and local context information at the same time, which improves the detection ability of the algorithm for small targets in complex scenes. …”
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From rare to recognized: enhanced detection uncovers Cryptosporidium endemicity and species diversity in Denmark by Tine Graakjær Larsen, Steen Ethelberg, Hans Linde Nielsen, Gitte Nyvang Hartmeyer, Lene Nielsen, Mike Zangenberg, Jonas Kähler, Jørgen Harald Engberg, Christen Rune Stensvold

“…After 2021, the number of new cases increased substantially, coinciding with the adoption of gastrointestinal syndromic testing in several local hospitals. During seasonal peaks (August-October), Cryptosporidium was detected in the stool of >2% of patients tested. …”
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Enhancing Facial Feature Detection: Hybrid Active Shape and Active Appearance Model (HASAAM) by Musab Iqtait, Jafar Ababneh, Mohammad Rasmi, Amer Abu-Jassar, Suhaila Abuowaida

“…In order to prevent AAM from fitting in order to address the local minima problem, ASM was used to identify these exterior landmarks of the face. …”
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Acute Psychological Stress Detection Using Explainable Artificial Intelligence for Automated Insulin Delivery by Mahmoud M. Abdel-Latif, Mudassir M. Rashid, Mohammad Reza Askari, Andrew Shahidehpour, Mohammad Ahmadasas, Minsun Park, Lisa Sharp, Lauretta Quinn, Ali Cinar

“…The SHAP technique is also used to explain the local signal importance for particular instances of misclassified samples. …”
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