Review of Multivariate Time Series Clustering Algorithms by ZHENG Desheng, SUN Hanming, WANG Liyuan, DUAN Yaoxin, LI Xiaoyu

“…Initially, based on classification standards such as feature extraction methods, similarity measurement algorithms, and clustering partition frameworks, this paper conducts a comparative analysis of existing multivariate time series clustering algorithms. …”
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DScanNet: Packaging Defect Detection Algorithm Based on Selective State Space Models by Yirong Luo, Yanping Du, Zhaohua Wang, Jingtian Mo, Wenxuan Yu, Shuihai Dou

“…For this reason, an improved target detection model, DScanNet, is proposed in this paper. To address the problem that the model’s detailed feature extraction for small target defects is not sufficient and thus leads to low detection accuracy, the MEFE module, the local feature extraction module (LFEM Block), and the PCR module of the multi-scale convolution and feature enhancement strategy are proposed to enhance the model’s capability of capturing defective features and focusing on specific features, and to improve the detection accuracy. …”
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KNEE OSTEOARTHRITIS STAGE CLASSIFICATION BASED ON HYBRID FUSION DEEP LEARNING FRAMEWORK by Delveen Luqman Abd Alnabi, Shereen Sh Ahmed, Nisreen Luqman Abd Alnabi

“…The feature-level, decision-level, score-level, and meta-based fusion technologies were also performed on the outputs of the best three trained models to minimize the individual models’ errors. …”
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WCANet: An Efficient and Lightweight Weight Coordinated Adaptive Detection Network for UAV Inspection of Transmission Line Accessories by Jiawei Chen, Pengfei Shi, Mengyao Xu, Yuanxue Xin, Xinnan Fan, Jinbo Zhang

“…The network is designed with a plug-and-play WCA module that can effectively identify dense small targets, retain information in each channel, and reduce computational overheads, while incorporating Sim-AFPN with a skip-connection structure into the network aggregate feature information layer by layer, enhancing the ability to capture key features, and achieving a lightweight network structure. …”
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Enhanced Plant Leaf Classification over a Large Number of Classes Using Machine Learning by Ersin Elbasi, Ahmet E. Topcu, Elda Cina, Aymen I. Zreikat, Ahmed Shdefat, Chamseddine Zaki, Wiem Abdelbaki

“…Features are extracted based on the margin, texture, and shape of the leaves. …”
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Modern Organization of Financial Control by O. P. Umanet

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DAPSS: A Novel Network for DOM Assisted Oblique Photography Point Cloud Semantic Segmentation by Zhenzhen Song, Mingqiang Guo, Liang Wu, Heng Liu, Ying Huang, Zheng Liu

“…DAPSS not only effectively addresses the recognition of small-scale surface features, but also resolves the occlusion problems associated with projection-based methods.…”
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An Innovative Method of Monitoring Cotton Aphid Infestation Based on Data Fusion and Multi-Source Remote Sensing Using Unmanned Aerial Vehicles by Chenning Ren, Bo Liu, Zhi Liang, Zhonglong Lin, Wei Wang, Xinzheng Wei, Xiaojuan Li, Xiangjun Zou

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Genetic Algorithm-Enhanced Direct Method in Protein Crystallography by Ruijiang Fu, Wu-Pei Su, Hongxing He

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Data aggregation impacts on built environment-mode share models around public transit stations by Seyed Sajjad Abdollahpour, Huyen T. K. Le, Ralph Buehler, Steve Hankey

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Композиция и стилистические особенности современных храмовых мозаик by Пономарев, А.В.

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A Deep Learning-Driven Black-Box Benchmark Generation Method via Exploratory Landscape Analysis by Haoming Liang, Fuqing Zhao, Tianpeng Xu, Jianlin Zhang

“…Exploratory landscape analysis (ELA) offers a systematic framework for characterizing objective functions, based on quantitative landscape features. This study proposes a method for generating benchmark functions tailored to single-objective continuous optimization problems with boundary constraints using predefined ELA feature vectors to guide their construction. …”
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Patients’ experience of patient-reported outcomes, continuous feedback, and a solution-focused approach (using DIALOG +) in psychosis care in Sweden by Marcus Lundmark, Katarina Allerby, Andreas Gremyr, Ann-Christine Andersson

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Innovative hybrid algorithm for efficient routing of limited capacity vehicles by Vu Hong Son Pham, Van Nam Nguyen, Nghiep Trinh Nguyen Dang

“…This study addresses the critical challenges posed by the capacitated vehicle routing problem (CVRP), particularly in the logistics of cement transportation under capacity constraints. …”
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3D geometric moment invariants from the point of view of the classical invariant theory by L. P. Bedratyuk, A. I. Bedratyuk

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Research on Emotion Classification Based on Multi-modal Fusion by zhihua Xiang, Nor Haizan Mohamed Radzi, Haslina Hashim

“…However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. …”
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Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data by Bei Liu, Xiao Wang, Zhaoxin Zhang, Zhenjie Zhao, Xiaoming Wang, Ting Liu

“…Then, the CNN-LSTM network is used to predict time series data, and the GAN is used to expand fault data samples to solve the problem of an unbalanced data distribution. Meanwhile, a multi-scale feature extraction network with time–frequency information is designed to improve the accuracy of fault detection. …”
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Research on traffic representation in network anomaly detection by SUN Jianwen, ZHANG Bin, CHANG Heyu

“…Aiming to address the problem of information loss in traffic representation for network anomaly detection, the impact of feature information dimension of different traffic representation on anomaly detection performance was analyzed from the perspective of data collection granularity. …”
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DBN Face Recognition Algorithm Based on GCSLBP by GUAN Xiao-rui, CHENG Wei-yue, ZHANG Xue-qin, LIN Ke-zheng, GAO Tie-hong

“…Aiming at the problem that the feature vector extracted by original Gabor transform has a high dimension and DBN ignores local information when completing face recognition, a DBN face recognition algorithm based on GCSLBP is proposed. …”
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Optimization of Parallax Image Projection Based on SIFT by WANG Yang, LIU Jie, YOU Pinhong

“…In order to solve the problem of misalignment and ghosting in image stitching due to large parallax, this paper proposes a parallax image projection optimization algorithm based on SIFT First, the feature points of the image are acquired through SIFT, and then the mismatched points are removed from the image by the random sampling consistency algorithm, and the projected matrix calculation is performed on the removed feature points. …”
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