LGR-Net: A Lightweight Defect Detection Network Aimed at Elevator Guide Rail Pressure Plates by Ruizhen Gao, Meng Chen, Yue Pan, Jiaxin Zhang, Haipeng Zhang, Ziyue Zhao

“…The experimental results show that LGR-Net outperforms other YOLO-series models in terms of overall performance, achieving optimal results in terms of precision (<i>p</i> = 98.7%), recall (R = 98.9%), mAP (99.4%), and parameter count (2,412,118). LGR-Net achieves low computational complexity and high detection accuracy, providing an efficient and effective solution for defect detection in elevator guide rail pressure plates.…”
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Machine learning based predictive insights into compressive strength and strength retention of magnesium oxychloride cement by Ahmad Nawaz, M. Zohaib Nawaz, Leyang Lv, Yingwu Zhou

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Distributional properties of the entropy transformed Weibull distribution and applications to various scientific fields by Tabassum Naz Sindhu, Anum Shafiq, Showkat Ahmad Lone, Qasem M. Al-Mdallal, Tahani A. Abushal

“…Some of its core characteristics, such as its statistical and computational features, are simply and clearly presented. …”
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Similarity measure for intuitionistic fuzzy sets and its applications in pattern recognition and multimodal medical image fusion by Anjali Patel, Deepa Gupta, E. A. Gopalakrishnan, Divya Sasidharan, V. Sowmya, Mohammed Zakariah, Abdulaziz S. Almazyad

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A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

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Analysis and performance evaluation of non-toxic organo-metal halide (CH3NH3SnI3) perovskite optical absorber based photovoltaic cell by Azka Khalid, Muhammad Imran Malik, Irfan Qasim

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A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

“…The experimental results showed that the proposed algorithm achieved 98.9% accuracy, with 2.1 million parameters and a computational cost of 7.0 GFLOPs. Compared to other methods, our approach outperforms them in both performance and efficiency, fulfilling the real-time and precise defect detection needs of photodetectors.…”
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Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries by Yuanchen Cheng, Zichen Zhang, Yuqing Liu, Jie Li, Zhou Fu

“…Experimental results show that the improved YOLOv8n-DMTNet model achieves a 9.2% increase in mAP@0.5 and a 6.4% increase in mAP@0.5:0.95 compared to YOLOv8n in the tuna detection task, while reducing the number of parameters by 42.3% and computational complexity by 33.3%. …”
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Design of an Intelligent Pear Bagging End-Effector Based on Yolov8 and SGBM Algorithm by Jing Ruijun, Liu JingKai, LiXin, ZhiguoZhao

“…We describe an intelligent bagging end-effector for pears, which employs the Yolov8 algorithm for fruitlets detection and the Semi-Global Block Matching (SGBM) algorithm to acquire three-dimensional spatial information of the targets. To address the computational limitations of embedded devices in agricultural intelligent equipment, we improve the YOLOv8 model by replacing its neck component with the Asymptotic Feature Pyramid Network (AFPN) and incorporating Context Guided (CG) blocks into the C2f module. …”
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Enhanced IoT-Based Face Mask Detection Framework Using Optimized Deep Learning Models: A Hybrid Approach With Adaptive Algorithms by Parul Dubey, Pushkar Dubey, Celestine Iwendi, Cresantus N. Biamba, Deepak Dasaratha Rao

“…In the present study, a hybrid Flame-Sailfish Optimization (HFSO)-based deep learning framework is proposed. It combines the feature extraction capabilities of ResNet50 with the efficiency of MobileNetV2. …”
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BiSeNeXt: a yam leaf and disease segmentation method based on an improved BiSeNetV2 in complex scenes by Bibo Lu, Yanjun Lu, Di Liang, Jie Yang

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Ground-Based Remote Sensing Cloud Image Segmentation Using Convolution-MLP Network by Shuang Liu, Jiafeng Zhang, Zhong Zhang, Shuzhen Hu, Baihua Xiao

“…To this end, we propose the attention-guided MLPs module to highlight salient features and suppress irrelevant features from the spatial and channel aspects. …”
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Dual-Path Beat Tracking: Combining Temporal Convolutional Networks and Transformers in Parallel by Nikhil Thapa, Joonwhoan Lee

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Semantic Segmentation of Unmanned Driving Scene Based on Spatial Channel Dual Attention by WANGXiaoyu, LINPeng

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scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data by Lin Yuan, Zhijie Xu, Boyuan Meng, Lan Ye

“…First, they do not fully exploit cellular features. Second, they are developed based on gene expression information and lack of flexibility in integrating intercellular relationships. …”
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Innovative Ghost Channel Spatial Attention Network with Adaptive Activation for Efficient Rice Disease Identification by Yang Zhou, Yang Yang, Dongze Wang, Yuting Zhai, Haoxu Li, Yanlei Xu

“…Additionally, the model incorporates the Ghost Module as a replacement for traditional 1 × 1 convolutions, further reducing computational overhead. Innovatively, we introduce a Channel Spatial Attention Mechanism (CSAM) that significantly enhances feature extraction and generalization aimed at rice disease detection. …”
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Perturbative analysis of Casimir wormholes with generalized uncertainty principle corrections in matter-geometry coupled gravity by Zinnat Hassan, Saddam Hossain, Satyendra Nath Barman, P. K. Sahoo

“…Furthermore, we examine the light deflection angle associated with the wormhole geometry, providing additional insights into its observational features. Our results suggest that, under appropriate conditions, Casimir wormholes can theoretically exist as stable and traversable structures within this modified gravity framework.…”
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Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data by Arkadiusz Syta, Arkadiusz Podkowiński, Tomasz Chorągiewicz, Robert Karpiński, Jakub Gęca, Dominika Wróbel-Dudzińska, Katarzyna E Jonak, Dariusz Głuchowski, Marcin Maciejewski, Robert Rejdak, Kamil Jonak

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Comparison of the First Three Waves of the COVID-19 Pandemic in Russia in 2020–21 by L. S. Karpova, K. A. Stolyarov, N. M. Popovtseva, T. P. Stolyarova, D. M. Danilenko

“…Compare the intensity of three waves of the COVID-19 pandemic in Russia. To identify the features of the parameters of the COVID-19 pandemic in Russia in the age groups of the population and in the federal districts. …”
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Design and Research of Low-Cost and Self-Adaptive Terrestrial Laser Scanning for Indoor Measurement Based on Adaptive Indoor Measurement Scanning Strategy and Structural Characteri... by Zhongyue Zhang, Huixing Zhou, Shun Wang, Chongwen Xu, Yannan Lv

“…This paper mainly presents two parts of innovations: (1) for planning of scanning, the novel TLS features planning sampling density of scanning according to room size and converting scanning data from poses to point clouds, and (2) for processing of point clouds, this paper proposes two novel segmentation algorithms, namely, “on-boundary segmentation algorithm” and “on-angular-distance segmentation algorithm,” based on indoor spatial structure features and characteristics of TLS. …”
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