Lightweight rice leaf spot segmentation model based on improved DeepLabv3+ by Jianian Li, Long Gao, Xiaocheng Wang, Jiaoli Fang, Zeyang Su, Yuecong Li, Shaomin Chen

“…Second, based on Haar wavelet downsampling, a multi-scale detail enhancement (MSDE) module was proposed to improve decision-making ability of the model in transitional regions such as spot gaps, and to improve the sticking and blurring problems at the boundary of spot segmentation. Meanwhile, the PagFm-Ghostconv Feature Fusion (PGFF) module was proposed to significantly reduce the computational overhead of the model. …”
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The Inverse Scattering of Three-Dimensional Inhomogeneous Steady-State Sound Field Models by Zhaoxi Sun, Wenbin Zhang, Meiling Zhao

“…Through an innovative sliced data processing strategy, the 3D reconstruction problem is decomposed into a combination of 2D problems, thereby significantly reducing the computational cost. …”
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SAR Target Depression Angle Invariant Recognition of Few-Shot Learning Via Dense Graph Prototype Network by Xiangyu Zhou, Yuhui Zhang, Qianru Wei

“…DGP-Net addresses the feature deviation problem by learning potential features and utilizes feature distribution modeling for classification. …”
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Clinical Applicability of Machine Learning Models for Binary and Multi-Class Electrocardiogram Classification by Daniel Nasef, Demarcus Nasef, Kennette James Basco, Alana Singh, Christina Hartnett, Michael Ruane, Jason Tagliarino, Michael Nizich, Milan Toma

“…They exhibit strong convergence and robust feature importance rankings, with ventricular rate, QRS duration, and P-R interval identified as key predictors. …”
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Automatic picking method for ground penetrating radar wave groups at rough coal-rock interfaces by Ying TIAN, Chunzhi LI, Shuo CHEN, Zihao WANG, Fuyan LYU, Qiang ZHANG, Meng HAN, Chengjun HU

“…The method also employs a RANSAC iterative fitting algorithm and waveform feature matching to classify and identify interfering hyperbolas and coal-rock interface curves. …”
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Specificity of political issues in J. Rotrou’s tragedy "Iphigenie in Aulis" (1640) by Larisa Simonova

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On $ \left(\mathit{p}, \mathit{q}\right) $-fractional linear Diophantine fuzzy sets and their applications via MADM approach by Hanan Alohali, Muhammad Bilal Khan, Jorge E. Macías-Díaz, Fahad Sikander

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ENVIRONMENTAL AND HYDRO /ECO NOMICASSESSMENT AS A TOOL FOR MANAGING WATER USE AND LIFE QUALITY OF POPULATION IN RURAL TERRITORIES OF ALTAI KRAY by Elena S. Orlova, Irina D. Rybkina

“…Each of them is characterized by the common features of water sector development.…”

Resource-Constrained Specific Emitter Identification Based on Efficient Design and Network Compression by Mengtao Wang, Shengliang Fang, Youchen Fan, Shunhu Hou

“…To tackle these problems, we propose an RC-SEI method based on efficient design and model compression. …”
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Novel hybrid intelligence model for early Alzheimer's diagnosis utilizing multimodal biomarker fusion by Shehu Mohammed, Neha Malhotra, Arun Singh, Awad M. Awadelkarim, Shakeel Ahmed, Saiprasad Potharaju

“…The database comprises 35 demographic, behavioral, and clinical features. Feature selection procedures produced key predicting variables (i.e., MMSE scores, performance in Activities of Daily Living (ADL), cholesterol level, and behavior problems). …”
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A probabilistic neural network-based bimanual control method with multimodal haptic perception fusion by Xinrui Chi, Zhanbin Guo, Fu Cheng

“…In the master-slave robot system, single-modal tactile perception has problems such as collision detection delay (>120 ms), force estimation error (>2.3 N), and sensor conflicts, resulting in a 37 % failure rate of robot operations in nuclear decommissioning scenarios and a 19.2 % risk of excessive tissue compression in laparoscopic surgery. …”
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AC contactor fault recognition based on ERF and BO-SVC by LIU Shuxin, QI Xinzhi, LYU Xianfeng

“…Following the feature extraction step, the selected optimal features are fed into BO-SVC recognition model. …”
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Multi-Scale Fusion Lightweight Target Detection Method for Coal and Gangue Based on EMBS-YOLOv8s by Lin Gao, Pengwei Yu, Hongjuan Dong, Wenjie Wang

“…This structure can fully utilize the features of different scales, improve the model’s detection accuracy, and reduce its complexity. …”
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Multi-scale target intelligent detection method for coal, foreign object and early damage of conveyor belt surface under low illumination and dust fog by Hongwei FAN, Jinpeng LIU, Xiangang CAO, Chao ZHANG, Xuhui ZHANG, Man LI, Hongwei MA, Qinghua MAO

“…Then, aiming at the problem of insufficient feature extraction ability of backbone network, a new P_Res2Block multi-scale feature representation module is constructed by using Partial Conv and Res2Net, and it is used to replace the Bottleneck of C3 module in backbone network to obtain a new P_RC3 lightweight multi-scale feature extraction module, so as to increase the receptive field of the model and enhance the attention to small targets. …”
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MOVING OBJECT DETECTION USING DISCRETE COSINE TRANSFORM BASED BACKGROUND SUBTRACTION by Sharmistha Puhan, Sambit Kumar Mishra, Deepak Kumar Rout

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APPLICATION OF SEMI SUPERVISED LAPLACE SCORE IN ROLLING BEARING FAULT DIAGNOSIS (MT) by LIANG Chuang, CHEN ChangZheng, LIU Ye, JIA XinYing

“…Aiming at the problem of insufficient labeled samples in the process of rolling bearing fault diagnosis, a rolling bearing fault diagnosis model based on semi supervised Laplace score（SSLS） and kernel principal component analysis（KPCA） is proposed by combining with the idea of feature selection and secondary mining. …”
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Epic Synthesis in Late Work of I. S. Turgenev by V. G. Andreeva

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CCDR: Combining Channel-Wise Convolutional Local Perception, Detachable Self-Attention, and a Residual Feedforward Network for PolSAR Image Classification by Jianlong Wang, Bingjie Zhang, Zhaozhao Xu, Haifeng Sima, Junding Sun

“…Subsequently, replacing the conventional feedforward network with a residual feedforward network that incorporates residual structures aids the model in better representing local features, further enhances the capability of cross-layer gradient propagation, and effectively alleviates the problem of vanishing gradients during the training of deep networks. …”
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Semi-natural modelling in the analysis of the discriminatory characteristics of the image sensor with the exponential correlation function by Vladimir Pavlovich Gerasimov, Vladimir Danilovich Kovalyov, Sergey Vladimirovich Gerasimov, Alexander Yur'yevich Darzhanija

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The Hybrid Model of Multivariate Index Analysis of Current Assets by Alexander Nickolaevich Tsatsulin

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