Ground Fissure Identification in Mining Areas from UAV Images Based on DN-CAMSCBNet by Haibin Hu, Xinhui Guo, Jie Xiao

“…To mitigate the damage to the ecological environment caused by mining areas and ensure sustainable long-term resource exploitation, it is of particular importance to identify ground fissures in mining areas efficiently. Therefore, this paper proposes a ground fissure identification model for UAV images in mining areas named DN-CAMSCBNet. …”
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Recursive Method in Modal Parameter Identification of Aerospace Structures under Non-Gaussian Noise by Lei Yu, Yong-li Zhang, Meng-di Yuan, Rui-qing Liu, Qi Zhang

“…Finally, steps of the identification procedure and model selection are presented. …”
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Investigating the Role of Fan- Team Identification in the Sponsorship Consequences in Professional Football League of Iran by Akbar Jaberi, Zahra Barkhordar

“…In other words, strengthening the fan-team identification level can improve the sponsorship consequences in Professional Football League in Iran.Conclusion: According to the importance of fan-team identification in sponsorship consequences, sport marketers as well as corporates that are active in sport events, will be able to be more efficient in sport context by concentrating on identification concept.…”
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Non-destructive Identification of Moldy Walnuts by Fusing X-Ray and Visual Image Features by NING Xinyue, ZHANG Hui, JI Shuai, LAI Lisi

“…On this basis, an extreme learning machine (ELM) model and a K-nearest neighbors (KNN) model were developed for moldy walnut classification, and the performance of the classification models under different feature sets was compared through experiments to verify the feasibility of fusing X-ray and visual image features for detecting moldy walnuts. …”
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Vehicle load identification based on bridge response using deep convolutional neural network by Sadaqat Hussain, Syed M. Hussain, Yu Xin, Zuo-Cai Wang

“…The results reveal that the Inception model excelled in vehicle load identification, achieving an impressive validation accuracy of 99.9%. …”
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GC-MT: A Novel Vessel Trajectory Sequence Prediction Method for Marine Regions by Haixiong Ye, Wei Wang, Xiliang Zhang

“…To ensure the safety of maritime traffic and enhance the efficiency of navigation information, vessel trajectory prediction is crucial for Automatic Identification Systems (AIS). …”
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Inversion Method Based on Temporal Convolutional Networks for Random Ice Load on Conical Offshore Platforms by Wei Li, Ya Guo, Shuzhao Li, Yang Gao, Yan Qu

“…This work represents the first application of TCN to ice load identification. By combining it with simulation data, we offer a high-precision, data-driven approach for dynamic load identification, enhancing the efficiency and reliability of safety assessments for conical offshore platforms.…”
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Enhancing biometric identification using 12-lead ECG signals and graph convolutional networks by Maram Al Alfi, Pedro Peris-Lopez, Carmen Camara

“…This index is used to construct a graph representation, where nodes correspond to ECG features and edges reflect their relationships based on MI values. The GCN model is trained on this graph, enabling it to learn complex patterns for user identification efficiently.ResultsExperimental results demonstrate that the proposed GCN-MI model achieves 100% accuracy with a 5-layer architecture at a k-fold of 75, outperforming conventional approaches that require less training data.DiscussionThis work introduces several innovations: the integration of MI indices enhances feature selection, improving model robustness and efficiency; the graph-based learning framework effectively captures both spatial and statistical relationships within ECG data, leading to higher classification accuracy; the proposed approach offers a scalable and real-time biometric authentication system suitable for applications in finance, healthcare, and personal device access. …”
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Pest Identification and Counting of Yellow Plate in Field Based on Improved Mask R-CNN by Minxi Rong, Zhizheng Wang, Bin Ban, Xiaoli Guo

“…Therefore, this paper proposes an object detection algorithm based on the improved Mask R-CNN model, aiming to improve the accuracy and efficiency in pest identification and counting. …”
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Applying Machine Learning for Sustainable Farm Management: Integrating Crop Recommendations and Disease Identification by P. Ankit Krishna, Neelamadhab Padhy, Archana Patnaik

“…CNN, the illness identification system, attained an impressive 96.06% accuracy rate. …”
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Autoencoder-Driven Fiducial Landmark Identification in 3D Brain MRI for Neuroimaging Alignment by G. Deepali, H. Anitha, B. P. Swathi, M. V. Suhas

“…This method offers a scalable and efficient solution for clinical and research applications, facilitating more reliable head modeling, source localization, and multimodal image integration.…”
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Research on Binary Mixed VOCs Gas Identification Method Based on Multi-Task Learning by Haixia Mei, Ruiming Yang, Jingyi Peng, Keyu Meng, Tao Wang, Lijie Wang

“…Comparative experiments reveal that using only 35% of the total data length as input data yields excellent identification performance. Moreover, multi-task learning effectively integrates feature information across tasks, significantly improving model efficiency compared to single-task learning.…”
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Encapsulation Based Method for Natural Frequency Identification of Deployable Solar Arrays with Multiple Plates by Chunjuan Zhao, Xiangyu Zhao, Shanbo Chen, Jisong Yu, Lei Zhang

“…Second, the mathematical model of the test system is established. Abstracting parts of the parameters of the test object into an encapsulated entity, the mathematical model is simplified by equivalent variables. …”
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Computer Vision-Based Robotic System Framework for the Real-Time Identification and Grasping of Oysters by Hao-Ran Qu, Jue Wang, Lang-Rui Lei, Wen-Hao Su

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Validation of Methods of Identification and Quantitative Determination of Active Ingredients in Films for Treatment of Caries of Dentin by E. S. Berezina, A. L. Golovanenko, I. V. Alekseeva

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Visible-infrared person re-identification with region-based augmentation and cross modality attention by Yuwei Guo, Wenhao Zhang, Licheng Jiao, Shuang Wang, Shuo Wang, Fang Liu

“…In this paper, a novel Region-based Augmentation and Cross Modality Attention (RACA) model is proposed, focusing on the pedestrian regions to efficiently compensate for missing modality-specific features. …”
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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

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Identification method for malicious traffic in industrial Internet under new unknown attack scenarios by ZENG Fanyi, MAN Dapeng, XU Chen, HAN Shuai, WANG Huanran, ZHOU Xue, LI Xinchun, YANG Wu

“…Aiming at the problem of traffic data distribution shift caused by new unknown attacks in the industrial Internet, a malicious traffic identification method based on neighborhood filtering and stable learning was proposed to enhance the effectiveness and robustness of the existing graph neural network model in identifying known malicious traffic. …”
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Identification method for malicious traffic in industrial Internet under new unknown attack scenarios by ZENG Fanyi, MAN Dapeng, XU Chen, HAN Shuai, WANG Huanran, ZHOU Xue, LI Xinchun, YANG Wu

“…Aiming at the problem of traffic data distribution shift caused by new unknown attacks in the industrial Internet, a malicious traffic identification method based on neighborhood filtering and stable learning was proposed to enhance the effectiveness and robustness of the existing graph neural network model in identifying known malicious traffic. …”
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Identification of Tool-Wear State Using Information Fusion and SSA–BP Neural Network by Zishuo Wang, Hongwei Cui, Shuning Liang, Tao Ding, Xingquan Gao

“…Lastly, a tool-wear-state identification model based on the SSA–BP neural network is constructed. …”
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