Zero-shot classification with multi-model information interaction and its application in Mars exploration scenarios by TAN Xiaomeng, XI Bobo, XUE Changbin, LI Yunsong

“…The research content was mainly divided into two aspects: dataset construction and algorithm research. In terms of dataset construction, the zero-shot classification dataset for Mars exploration was integrated and reconstructed. …”
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Topology identification and parameters estimation of LV distribution networks using open GIS data by Dong Liu, Juan S. Giraldo, Peter Palensky, Pedro P. Vergara

“…., distributed energy resources (DERs) integration, network hosting capacity analysis, state estimation, and electric vehicle charging management. …”
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Regional Short‐Term Wind Power Prediction Based on CEEMDAN‐FTC Feature Mapping and EC‐TCN‐BiLSTM Deep Learning by Guoyuan Qin, Xiaosheng Peng, Zimin Yang

“…First, the regional input features, encompassing data from numerous wind farms, are decomposed using the CEEMDAN algorithm to extract intrinsic mode functions (IMFs) and residuals at different time scales. …”
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Improved model MASW YOLO for small target detection in UAV images based on YOLOv8 by Xianghe Meng, Fei Yuan, Dexiang Zhang

“…Abstract The present paper proposes an algorithmic model, MASW-YOLO, that improves YOLOv8n. …”
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Sparse point spread function-based multi-image optical encryption by Ning Xu, Dalong Qi, Long Cheng, Zhen Pan, Chengyu Zhou, Wenzhang Lin, Hongmei Ma, Yunhua Yao, Yuecheng Shen, Lianzhong Deng, Zhenrong Sun, Shian Zhang

“…During decryption, an iterative algorithm recovers encrypted images with improved reconstruction quality. …”
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Velocity-Constraint Kalman Filtering for Enhanced Bubble Tracking in Motion-Compensated Ultrasound Localization Microscopy by Yifei Zhu, Lingyin Jiang, Qi Zhang, Jun Yin, Bingze Du, Guofeng Zhang, Haijun Zhang, Bo Ding, Han Lin, Honghui Xue, Xiasheng Guo, Xiao-Yang Zhang, Jing-Ning Zhu, Dong Zhang, Juan Tu, Ning Gu

“…To address these issues, an enhanced ULM approach (shorten as vc-Kalman) integrating rapid motion compensation was developed to achieve excellent image quality. …”
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Artificial Intelligence in Placental Pathology: New Diagnostic Imaging Tools in Evolution and in Perspective by Antonio d’Amati, Giorgio Maria Baldini, Tommaso Difonzo, Angela Santoro, Miriam Dellino, Gerardo Cazzato, Antonio Malvasi, Antonella Vimercati, Leonardo Resta, Gian Franco Zannoni, Eliano Cascardi

“…Finally, we outline future research directions, emphasizing the refinement of AI algorithms for routine clinical integration and fostering interdisciplinary cooperation among pathologists, computational researchers, and clinical specialists.…”
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Remote Sensing Time Series Analysis: A Review of Data and Applications by Yingchun Fu, Zhe Zhu, Liangyun Liu, Wenfeng Zhan, Tao He, Huanfeng Shen, Jun Zhao, Yongxue Liu, Hongsheng Zhang, Zihan Liu, Yufei Xue, Zurui Ao

“…The high-frequency new data, i.e., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. …”
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AI-Driven Precision: Transforming Below-Knee Amputation Care in Modern Healthcare by Sarah Duraid AlQaissi, Ahmed A.A. AlDuroobi, Abdulkader Ali. A. Kadaw

“…In this study, a three-dimensional model of the residual limb for a patient with transtibial amputation was realized with the integration of artificial intelligence and a computer vision approach demonstrating the benefits of AI segmentation tools and artificial algorithms to generate higher accuracy three-dimensional model before prosthetic socket design or in case of comparison the 3D model generated from MRI with another 3D model generated from another technique, where a residual limb of a 23 years old male patient with amputation in the left leg wearing a prosthetic socket liner, and having 62 kg weight, 168 cm height, with high activity level. …”
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Cloud-magnetic resonance imaging system: In the era of 6G and artificial intelligence by Yirong Zhou, Yanhuang Wu, Yuhan Su, Jing Li, Jianyu Cai, Yongfu You, Jianjun Zhou, Di Guo, Xiaobo Qu

“…Then, the data are uploaded to the cloud or edge nodes for fast image reconstruction, neural network training, and automatic analysis. …”
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Registration of Aerial Images and LiDAR Point Clouds by Exploiting Global–Local Geometric Constraints of Buildings by Wen Li, Min Chen, Meixi Huang, Han Hu, Tong Fang, Xuming Ge, Qing Zhu, Bo Xu, Gui Gao

“…Reliable registration of aerial images and airborne LiDAR point clouds (ALS) is challenging during the integrated three-dimensional reconstruction of the two types of data. …”
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Fusing multiplatform topo-bathymetric point clouds based on a pseudo-grid model: A case study around Ganquan Island, South China sea by Fanlin Yang, Xiaolin Yu, Xiankun Wang, Xiaozheng Mai, Chunxiao Wang, Anxiu Yang, Dianpeng Su

“…The results show that the proposed algorithm can achieve ideal results in terms of the average root mean square error (RMSE) of the six reference samples, which is reduced from 0.41 m to 0.19 m. …”
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Визначення кількісних і якісних показників доступного житла з урахуванням розміщення в місті by Kateryna Spasichenko

“…The importance of an integrated approach in the analysis of master plans of cities, neighborhoods, to identify vacant land for new construction, completion of affordable housing, and finding opportunities for reconstruction and renovation for affordable housing. …”
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GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…In the study of GNSS-PWV prediction, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm within a decomposition–integration framework effectively addresses the non-stationarity and complexity of PWV sequences, enhancing prediction accuracy. …”
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A Random Degradation Aggregation Network With Temporal-Spatial Attention for Satellite Video Super-Resolution by Lu Li, Mi Wang, Yingdong Pi

“…Moreover, current VSR algorithms are primarily designed for natural scene videos and fail to account for the unique characteristics of satellite videos, leading to suboptimal reconstruction performance when directly applied to them. …”
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Clinical applications of photon-counting CT in neuroimaging by LÜ Haiying, LU Yong, HE Naying

“…In addition, UHR-PCCT significantly outperforms conventional energy-integrating detector CT (EID-CT) in identifying aneurysm irregularity, aneurysm wall, and intraluminal features. …”
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Optimized fiducial marker placement using B‐spline surface modeling and graph theory for Cyberknife stereotactic body radiotherapy for superficial tumors by Jing Huang, Xianlong Xiong, Cheng Chen, Yuhan Li, Ruijie Wang, Zhitao Dai

“…Candidate points were filtered using multi‐criteria constraints: (1) a minimum of 18‐mm inter‐marker distance, (2) angular separation >30°, and (3) nonoverlapping visibility in 45° oblique digital reconstructed radiographs. To enhance the computational efficiency, a kd‐tree spatial indexing structure was integrated with graph theory, specifically the Bron–Kerbosch algorithm for maximal clique detection. …”
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Randomized comparison of AI enhanced 3D printing and traditional simulations in hepatobiliary surgery by Linqian Li, Shujie Cheng, Jinghua Li, Jihong Yang, Hongguang Wang, Bin Dong, Xiaoping Yin, Hongyun Shi, Shuo Gao, Feng Gu, Zhe Han, Zhi Chen, Jisen Zhao, Quan Zhang, Jie-Zhi Cheng, Yuan Wang, Fengwei Tan, Ke Zhang

“…Phase two utilized deep learning algorithms to optimize the 3D reconstruction process, significantly enhancing efficiency and accuracy compared to manual segmentation. …”
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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

“…The integrated SS-DWT framework significantly improves noise suppression, reduces musical noise artifacts, and enhances signal clarity as it leverages the strengths of both phase-aware spectral reconstruction in improved SS and phase-aware soft thresholding in DWT, particularly in adaptive noise refinement and thresholding. …”
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Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method by Ruxue Bai, Jinsong Li, Jinsong Liu, Yuetao Shi, Suoying He, Wei Wei

“…This study introduces an innovative hybrid model (HWGC-WPD-LSTM) that integrates an improved similar day algorithm (WGC: weighted grey correlation analysis and cosine similarity), Wavelet Packet Decomposition (WPD), and Long Short-Term Memory neural network (LSTM) for predicting day-ahead power output. …”
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