A Robust Method Based on Deep Learning for Compressive Spectrum Sensing by Haoye Zeng, Yantao Yu, Guojin Liu, Yucheng Wu

“…BEISTA-Net integrates the iterative shrinkage-thresholding algorithm (ISTA) with deep learning, thereby extracting and enhancing the block sparsity features of wideband spectrum signals, which significantly improves reconstruction accuracy. …”
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Automated Crack Width Measurement in 3D Models: A Photogrammetric Approach with Image Selection by Huseyin Yasin Ozturk, Emanuele Zappa

“…This study presents an automated system integrating photogrammetric 3D reconstruction with deep learning to quantify crack dimensions in a spatial context. …”
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Smart UAV-assisted rose growth monitoring with improved YOLOv10 and Mamba restoration techniques by Fan Zhao, Zhiyan Ren, Jiaqi Wang, Qingyang Wu, Dianhan Xi, Xinlei Shao, Yongying Liu, Yijia Chen, Katsunori Mizuno

“…We introduced MambaIR, a novel SRR algorithm based on selective state-space models, which significantly outperforms existing methods in enhancing low-resolution UAV imagery (PSNR: 28.34 dB, SSIM: 77.07 %). …”
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Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

“…Traditional low-rank decomposition methods aim to recover low-rank components and isolate sparse elements, but the structural integrity of the sparse components is often compromised. …”
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Petrophysics Parameter Inversion and Its Application Based on the Transient Electromagnetic Method by Xiaozhen Teng, Jianhua Yue, Kailiang Lu, Danyang Xi, Herui Zhang, Kua Wang

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Research on collision avoidance path planning method for mining and anchoring equipment in narrow and restricted space of tunneling laneways by Wenjuan YANG, Ran ZHANG, Xuhui ZHANG, Sihao TIAN, Zeyao WANG, Xili ZHENG, Zhiteng REN, Jicheng WAN, Yuyang DU, Hanbing ZHANG

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Integrating Multimodal Deep Learning with Multipoint Statistics for 3D Crustal Modeling: A Case Study of the South China Sea by Hengguang Liu, Shaohong Xia, Chaoyan Fan, Changrong Zhang

“…This study introduces a novel approach that integrates multimodal deep learning with multipoint statistics (MPS) to develop a high-resolution 3D crustal P-wave velocity structure model of the SCS. …”
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A Practical Methodology for Accuracy and Quality Evaluation of Structured Light Systems in Automotive Inspection by Antonio Lagudi, Umberto Severino, Loris Barbieri, Fabio Bruno

“…In the integration of structured light systems (SLSs) into automotive manufacturing pipelines, achieving reliable 3D reconstruction under industrial conditions remains a critical challenge. …”
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A Study on the Spatial Renewal of Atypical Traditional Villages Based on Modular Intelligent Grouping—Yuguang Village in China as an Example by Zao Li, Xiao Guo, Qiang Wang, Geng Cheng, Hanyue Tong

“…Therefore, taking Yuguang Village as an example, this paper proposes an efficient spatial renewal method: by analyzing the space of traditional villages, simulated villages, and modern villages, three modules of traditional “continuation”, transitional “integration”, and modern “reconstruction” are constructed, and the “discrete aggregation” algorithm is used to combine and simulate these modules in various ways. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…Variational mode decomposition (VMD) parameters are optimized via a novel exponential triangular optimization (ETO) algorithm to extract multi-scale features. Additionally, a refined TSMixer model is proposed, integrating reversible instance normalization (RevIn) to bolster the model’s generalizability and employing ETO to fine-tune model hyperparameters. …”
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Modified SLAM for Agricultural Robot Navigation by N. V. Gapon, V. V. Voronin, D. V. Rudoy, M. M. Zhdanova

“…To evaluate the impact on SLAM performance, the Stereo Multi-State Constraint Kalman Filter (S-MSCKF) algorithm was employed. Quantitative analysis of Absolute Trajectory Error (ATE) and mean RMSE was conducted both before and after applying the depth map reconstruction. …”
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Integrating LiDAR Point Cloud Classification and Building Footprints for Enhanced 3D LOD Building Modeling: A Deep Learning Approach by L. Lakshmanan, S. Nagarajan

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Investigation and Application of Water-Saving Monitoring Technology in Public Institutions by WANG Kang, ZHENG Yongjie, ZHANG Zhen, TANG Yanping, SONG Wenhao, GUO Xiaoming

“…Considering the characteristics of water use and the current situation of water facilities in public institutions,this study comprehensively employs the Internet of Things (IoT),cloud deployment,databases,three-dimensional (3D) visualization,and other advanced techniques to create a water-saving reconstruction scheme with integrated software and hardware for public institutions.Therefore,a smart water management platform for public institutions is built to implement advanced water-saving concepts and improve the water management level.The main research results are as follows:① By intelligent remote monitoring equipment,the multiclass water measurement network is designed to realize the fine collection of zonal water use data;② this study designs a reconstruction scheme of water facilities and explores the utilization mode of unconventional water sources to improve the utilization efficiency of water resources;③ multiple algorithms and statistical methods are used to analyze the time series of water use data,and thus this study realizes the analysis of pipeline network leakage and damage,identification of water use anomalies,and water-saving statistical analysis,and the investigation of water use laws;④ the platform with functions of monitoring and early warning is established to achieve real-time remote monitoring of water use,statistical analysis of historical water use,and identification and warning of pipe network leakage,so as to detect water anomalies in time and save water.The research results are first applied to the construction of the water-saving institution of the Pearl River Water Resources Commission to build a benchmark for the construction of water-saving institutions in the southern region.On the basis of application experience,the comprehensively integrated monitoring technology for water-saving in public institutions is developed,which provides a new idea for public institutions to save water.…”
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Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…Regulatory network reconstruction identified 32 transcription factors, 24 RNA-binding proteins, and 62 miRNAs as putative upstream regulators of key genes. …”
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An Integrated Fault Diagnosis Method for Rotating Machinery Based on Improved Multivariate Multiscale Amplitude-Aware Permutation Entropy and Uniform Phase Empirical Mode Decomposi... by Jiancheng Gong, Xiaoqiang Yang, Fan Pan, Wuqiang Liu, Fuming Zhou

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Rolling Bearing Fault Diagnosis Based on VMD-DWT and HADS-CNN-BiLSTM Hybrid Model by Luchuan Shao, Bing Zhao, Xutao Kang

“…The vibration signals are first reconstructed using a genetic algorithm (GA)-optimized VMD and particle swarm optimization (PSO)-optimized DWT for noise suppression. …”
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Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Results indicated that: 1) The reconstruction of cloud-free time series images with the Cloud Score+ method and the integrated NSPI and MNSPI approach was stable and effective, with correlation coefficients (<italic>r</italic>) exceeding 0.87 and low values for indicators such as root mean square error (RMSE), Robert&#x0027;s edge (Edges), and local binary patterns (LBP), meeting the requirements for paddy rice classification. 2) The classification accuracy of combining Sentinel-1 polarization features with Sentinel-2 spectral features could improve by up to 10.52% compared to before the combination. …”
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Implantation of an Artificial Intelligence Denoising Algorithm Using SubtlePET™ with Various Radiotracers: 18F-FDG, 68Ga PSMA-11 and 18F-FDOPA, Impact on the Technologist Radiation... by Jules Zhang-Yin, Octavian Dragusin, Paul Jonard, Christian Picard, Justine Grangeret, Christopher Bonnier, Philippe P. Leveque, Joel Aerts, Olivier Schaeffer

“…This study assesses the clinical deployment of SubtlePET™, a commercial AI-based denoising algorithm, across three radiotracers—¹⁸F-FDG, ⁶⁸Ga-PSMA-11, and ¹⁸F-FDOPA—with the goal of improving image quality while reducing injected activity, technologist radiation exposure, and scan time. …”
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Enhanced Short-Term PV Power Forecasting via a Hybrid Modified CEEMDAN-Jellyfish Search Optimized BiLSTM Model by Yanhui Liu, Jiulong Wang, Lingyun Song, Yicheng Liu, Liqun Shen

“…This study proposes a novel hybrid forecasting model that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the jellyfish search (JS) optimization algorithm, and a bidirectional long short-term memory (BiLSTM) neural network. …”
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NoiseAugmentNet-HHO: Enhancing Histopathological Image Classification Through Noise Augmentation by Prem Purusottam Jena, Debahuti Mishra, Kaberi Das, Sashikala Mishra

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