Closed-Loop Aerial Tracking with Dynamic Detection-Tracking Coordination by Yang Wang, Heqing Huang, Jiahao He, Dongting Han, Zhiwei Zhao

“…By implementing dynamic detection-tracking coordination with quality-aware feature preservation, our system enables real-time operation through performance-adaptive frequency modulation. …”
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Image-Based Iron Slag Segmentation via Graph Convolutional Networks by Wang Long, Zheng Junfeng, Yu Hong, Ding Meng, Li Jiangyun

“…To this end, we propose a novel spatial and feature graph convolutional network (SFGCN) module. …”
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EDRNet: Edge-Enhanced Dynamic Routing Adaptive for Depth Completion by Fuyun Sun, Baoquan Li, Qiaomei Zhang

“…Secondly, we design a Sparse Adaptive Dynamic Routing Transformer block called SADRT, which can effectively combine the global modelling capability of the Transformer and the local feature extraction capability of CNN. …”
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Quantum Positioning Scheme Based on Microwave–Optical Entanglement by Qiang Miao, Dewei Wu

“…Principles of microwave–optical entanglement preparation and our QPS scheme are introduced in detail. The entanglement feature, system stability and positioning feature of the scheme are analyzed after simulations. …”
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Research on Natural Language Misleading Content Detection Method Based on Attention Mechanism by Boning Liu

“…These models struggle particularly with ambiguous expressions, weak supervision, and multi-domain variability, resulting in reduced generalization and inconsistent performance. …”
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EFCNet enhances the efficiency of segmenting clinically significant small medical objects by Lingjie Kong, Qiaoling Wei, Chengming Xu, Xiaofeng Ye, Wei Liu, Min Wang, Yanwei Fu, Han Chen

“…Notably, smaller objects benefit most, highlighting EFCNet’s effectiveness where conventional models underperform. Unlike U-Net-Large, which offers marginal gains with increased scale, EFCNet’s superior performance is driven by its novel design. …”
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Explainable Survival Analysis of Censored Clinical Data Using a Neural Network Approach by Lisa Anita De Santi, Francesca Orlandini, Vincenzo Positano, Laura Pistoia, Francesco Sorrentino, Giuseppe Messina, Maria Grazia Roberti, Massimiliano Missere, Nicolò Schicchi, Antonino Vallone, Maria Filomena Santarelli, Alberto Clemente, Antonella Meloni

“…Classical approaches include the Kaplan–Meier estimator and Cox proportional hazards regression, which assume a linear relationship between the model’s covariates. However, the linearity assumption might pose challenges with high-dimensional data, thus stimulating interest in performing survival analysis using neural network models. …”
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A Comparative Analysis of Deep Learning-Based Segmentation Techniques for Terrain Classification in Aerial Imagery by Martina Formichini, Carlo Alberto Avizzano

“…Even though several existing networks have been used to study land segmentation using transfer learning methodologies, a comparative analysis of how the underlying network architectures perform has not yet been conducted. Since this scenario is different from the one in which these networks were developed, featuring irregular shapes and an absence of models, not all of them can be correctly transferred to this domain. …”
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Research and analysis of differential gene expression in CD34 hematopoietic stem cells in myelodysplastic syndromes. by Min-Xiao Wang, Chang-Sheng Liao, Xue-Qin Wei, Yu-Qin Xie, Peng-Fei Han, Yan-Hui Yu

“…After comprehensive evaluation, we ultimately selected three algorithms-Lasso regression, random forest, and support vector machine (SVM)-as our core predictive models. To more precisely pinpoint genes closely related to disease characteristics, we utilized the aforementioned three machine learning methods for prediction and took the intersection of these prediction results, yielding a more robust list of genes associated with disease features. …”
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Electrophysiological effects of kappa-opioid analgesic, RU-1205, using machine learning methods by K. Yu. Kalitin, O. Yu. Mukha, A. A. Spasov

“…Subsequently, machine learning methods were employed to reduce the dimensionality and extract connectivity features using the principal component analysis method, then a signal classification was performed (models based on Gaussian processes). …”
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Association between living alone and frailty, and its gender disparity: a multicenter cross-sectional study in Chinese older adults undergoing hospitalisation by Yuanyuan Jiang, Wenbin Wu, Hengshuo Liu, Qi Zhou, Huan Xi

“…Similar results were observed in fully adjusted models that controlled for age, marital status, and morbidity status. …”
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ANO5 p.I616F variant drives florid cemento-osseous dysplasia by disrupting transmembrane domain structure by Lanlan Zhang, Wenxi Jin, Yunfa Qin, Yonghui Zhang, Yemei Qian, Jingyi Li, Yu Liu, Yan’an Shi, Rongju Xie, Weihong Wang

“…Whole-exome sequencing was performed on a familial cohort (8 individuals). Identified variants were validated using Sanger sequencing. …”
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Targeting a cell state common to triple‐negative breast cancers by Markus K Muellner, Barbara Mair, Yasir Ibrahim, Claudia Kerzendorfer, Hannelore Lechtermann, Claudia Trefzer, Freya Klepsch, André C Müller, Ernestine Leitner, Sabine Macho‐Maschler, Giulio Superti‐Furga, Keiryn L Bennett, José Baselga, Uwe Rix, Stefan Kubicek, Jacques Colinge, Violeta Serra, Sebastian MB Nijman

“…We employed a multi‐omics approach and computational modeling to address the mechanism of action and identified spleen tyrosine kinase (SYK) as a novel and unexpected target in TNBC. …”
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Neuromorphic devices assisted by machine learning algorithms by Ziwei Huo, Qijun Sun, Jinran Yu, Yichen Wei, Yifei Wang, Jeong Ho Cho, Zhong Lin Wang

“…First, the basic structure of simple neuron models inspired by biological neurons and the information processing in simple neural networks are particularly discussed. …”
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Deep Learning in Food Image Recognition: A Comprehensive Review by Detianjun Liu, Enguang Zuo, Dingding Wang, Liang He, Liujing Dong, Xinyao Lu

“…Additionally, we analyze typical deep learning models and their performance on different datasets. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…To address these challenges, we propose a lightweight SAR small ship detection network, LWSARDet, which mitigates feature redundancy and reduces computational complexity in existing models. …”
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Design of a 25 MWe Solar Thermal Power Plant in Iran with Using Parabolic Trough Collectors and a Two-Tank Molten Salt Storage System by Aidin Alinezhad Kordmahaleh, Mohammad Naghashzadegan, Kourosh Javaherdeh, Mohammadreza Khoshgoftar

“…The varying types of collector dimensions have been investigated; then, by selecting autumnal equinox (22 September) at 12:00 PM as the design point, thermal performance of the solar power plant has been featured annually, in all conditions. …”
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The functions of punning utterances in English and Chinese: a cross-cultural perspective by Agnieszka Solska

“…Capitalizing on the universal linguistic feature of ambiguity, punning utterances can be found in languages as distinct as the Indo-European, marginally inflected English and the Sino-Tibetan, monosyllabic, inflectionless Chinese. …”
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A network-based approach on detecting dredgers’ illegal behavior of dumping dredged sediments by Rongxin Zhang, Fei Yuan, En Cheng

“…Local decision is made based on spectrum feature extraction and classification. In regard to the fusion center, a fusion strategy with a scanning window is adopted to make a system-level decision. …”
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Property Graph vs RDF Triple Store: A Comparison on Glycan Substructure Search. by Davide Alocci, Julien Mariethoz, Oliver Horlacher, Jerven T Bolleman, Matthew P Campbell, Frederique Lisacek

“…In this context, Graph databases are possible software solutions for storing glycan structures and Graph query languages, such as SPARQL and Cypher, can be used to perform a substructure search. Glycan substructure searching is an important feature for querying structure and experimental glycan databases and retrieving biologically meaningful data. …”
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