Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data by Mohammad Alemi, Alireza Bosaghzadeh, Fadi Dornaika

“…Lastly, most graph-based algorithms rely on affinity matrices that capture pairwise similarities across all data points, thus limiting their scalability to large-scale databases. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli, Rani Kumari, Adnan Akhunzada, Korhan Cengiz, Santosh Kumar Sharma, Rakesh Ranjan Kumar, Dinesh Kumar Sah

“…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …”
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Patient Specific Dosimetry Phantoms Using Multichannel LDDMM of the Whole Body by Daniel J. Tward, Can Ceritoglu, Anthony Kolasny, Gregory M. Sturgeon, W. Paul Segars, Michael I. Miller, J. Tilak Ratnanather

“…This paper describes an automated procedure for creating detailed patient-specific pediatric dosimetry phantoms from a small set of segmented organs in a child's CT scan. The algorithm involves full body mappings from adult template to pediatric images using multichannel large deformation diffeomorphic metric mapping (MC-LDDMM). …”
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Federated learning for digital twin applications: a privacy-preserving and low-latency approach by Jie Li, Dong Wang

“…Furthermore, variations in mapping bias across local devices and the presence of malicious clients can degrade FL training accuracy. …”
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Progressive multi-scale multi-attention fusion for hyperspectral image classification by Hu Wang, Sixiang Quan, Jun Liu, Hai Xiao, Yingying Peng, Zhihui Wang, Huali Li

“…The complementary responsibilities of the three branches address the issue of feature loss in details and improve the network’s learning efficiency across feature maps of different scales. By cleverly extracting features from different branches multiple times, the fusion of multi-scale features is achieved, avoiding the limitations of single-scale feature representation. …”
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Ultra-Short Baseline Synthetic Aperture Passive Positioning Based on Interferometer Assistance by Gaogao Liu, Qidong Zhang, Jian Xu, Jiangbo Zhu, Ziyu Huang, Beibei Mu, Hongfu Guo

“…Subsequently, the proposed step search (SS) algorithm based on cross-correlation analysis is used to obtain the receiving frequency of the single frequency signal, and the initial positioning distance is calculated using the corresponding mapping relationship based on this frequency. …”
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Extraction and location of subway shield tunnel segment joints from RMLS point clouds by Liying Wang, Ze You, Yong Feng, Chunxi Xie, Mahamadou Camara

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A Three-Dimensional Phenotype Extraction Method Based on Point Cloud Segmentation for All-Period Cotton Multiple Organs by Pengyu Chu, Bo Han, Qiang Guo, Yiping Wan, Jingjing Zhang

“…To address the challenge of significant structural variations in cotton organs across different growth stages, we designed an innovative point cloud segmentation algorithm, ResDGCNN, which integrates residual learning with dynamic graph convolution to enhance organ segmentation performance throughout all developmental stages. …”
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Causality research based on phase space reconstruction. by Lei Hu, Zhuoma Sunu, Hongke She, Binghuai Fan, Jingru Ma, Chaojiu Da

“…The phase space is then reconstructed, and the convergent cross-mapping algorithm is applied to analyse the causality between time series. …”
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Design and Application of Digital Twin-Based Brain Control System by Yinan Wang, Hongyang Jin, Zongwei Yao, Zhiyong Chang, Deping Wang

“…Despite the development and application of brain-computer interface (BCI) across various fields, this technology continues to face numerous challenges. …”
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Automated Detection of Tailing Impoundments in Multi-Sensor High-Resolution Satellite Images Through Advanced Deep Learning Architectures by Lin Qin, Wenyue Song

“…Accurate spatial mapping of Tailing Impoundments (TIs) is vital for environmental sustainability in mining ecosystems. …”
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A Convolutional Neural Network Model for Classifying Resting Tremor Amplitude in Parkinson’s Disease by Augusto Ielo, Serena Dattola, Lilla Bonanno, Paolo De Pasquale, Alberto Cacciola, Angelo Quartarone, Maria Cristina De Cola

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Observation optimization for marine target tracking by airborne and maritime unmanned platforms cooperation using adaptive enhanced dung beetle optimization by Qiuyang Dai, Faxing Lu, Haoran Shi, Junfei Xu, Jianjing Qu

“…To address these limitations, this paper proposes a heterogeneous unmanned platform cooperative observation optimization method based on Adaptive Enhanced Dung Beetle Optimization (AEDBO) algorithm. First, we derive optimal observation configurations for the aerial unmanned platform, maritime cooperative unmanned platform, and targets under azimuth systematic error impacts using an attitude correction algorithm. …”
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Hyper-LKCNet: Exploring the Utilization of Large Kernel Convolution for Hyperspectral Image Classification by Rong Liu, Zhilin Li, Jiaqi Yang, Jian Sun, Quanwei Liu

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Global positioning system (GPS) collar data shows variations in distribution, ranging area and habitat selection of the African savannah elephant in a semi-arid protected area by Nobert Tafadzwa Mukomberanwa, Phillip Taru, Beaven Utete, Patmore Ngorima

“…Minimum Convex Polygon method was employed to delineate elephant home ranges and the MaxEnt algorithm was used to model their habitat preferences. …”
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Unbiased High-Precision Cloud Detection for Advanced Himawari Imager Using Automatic Machine Learning by Bochun Liu, Jinming Ge, Qingyu Mu, Chi Zhang, Xiaoyu Hu, Jiajing Du, Yanyan Wu, Bo Wang, Xiang Li, Jianping Huang, Qiang Fu

“…The optimal algorithm achieves unbiased cloud detection across multiple surfaces by adjusting the output threshold of the mapping function, allowing for cloud detection results with varying confidence levels as required. …”
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Analyzing the applicability of psychometric QoE modeling for projection-based point cloud video quality assessment by Sam Van Damme, Jeroen van der Hooft, Filip De Turck, Maria Torres Vega

“…Results show the value of the sigmoidal mapping across all granularity levels. The clustering algorithm shows its value at the video-level and in the role of an outlier detector on the more fine-grained levels. …”
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Automated Localization and Classification of Expressway Pole-Like Road Facilities from Mobile Laser Scanning Data by Tran Thanh Ha, Taweep Chaisomphob

“…Second, the pole-like objects are extracted using horizontal cross section analysis and minimum vertical height criteria. …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…We derive a sample parameter correlation quantization matrix from oil chromatography fault data using association rules, which serves as the initial value for the NCA algorithm’s training metric matrix. The metric matrix obtained from training is then applied to perform a mapping transformation on the input data for the KNN classifier, thereby reducing the distance between similar samples and enhancing KNN classification performance. …”
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Jumping knowledge graph attention network for resource allocation in wireless cellular system by Qiushi Sun, Zhou Fang, Yin Li, Ovanes Petrosian

“…Extensive simulations demonstrate that the proposed algorithm significantly outperforms existing benchmark methods, exhibiting robust performance and strong generalization capabilities across a wide range of system parameter configurations.…”
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