A selection mechanism using multi-criteria evaluation and hierarhical classifying tree for resume data processing by O. V. German, J. O. German, S. Nasr

“…The paper considers a problem of optimal feature selection for resume data processing by means of combining multicriteria evaluation technique and hierarhical classifying trees technology what makes it possible to build a selection mechanism without necessity to collect data for the learning purposes of real applicants. …”
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A Small Object Detection Algorithm Integrated with ReFPN and Compound Attention Mechanism by ZHAO Yi-ming, WANG Jin-cong, REN Hong-e, ZHAO Long

“…To solve this problem, a feedback-based feature fusion network (ReFPN) for YOLOV4 algorithm was proposed.The original feature layer extracted from the backbone network is used twice to enhance the feature information of small targets and position regression performs more accurately. …”
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Research on defect perception model of distribution network based on big data analysis and waveform matching algorithm by LIN Kaifeng, LI Yiming, ZHANG Bo, YANG Changyu, ZHU Zeting, YANG Zhenda

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Sonar-Based Simultaneous Localization and Mapping Using the Semi-Direct Method by Xu Han, Jinghao Sun, Shu Zhang, Junyu Dong, Hui Yu

“…The SLAM problem is a common challenge faced by ROVs working underwater, with the key issue being the accurate estimation of pose. …”
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Multi-Modal MR Image Segmentation Strategy for Brain Tumors Based on Domain Adaptation by Qihong Yang, Ruijun Jing, Jiliang Mu

“…These measures mitigate the domain shift problem and improve the generalization ability of the model, enhancing the accuracy of multimodal brain tumor MR image segmentation.…”
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Memory‐ and time‐efficient dense network for single‐image super‐resolution by Nasrin Imanpour, Ahmad R. Naghsh‐Nilchi, Amirhassan Monadjemi, Hossein Karshenas, Kamal Nasrollahi, Thomas B. Moeslund

“…However, dense CNNs suffer from high memory usage due to the accumulation of concatenating feature‐maps stored in memory. To overcome this problem, a two‐step approach is proposed that learns the representative concatenating feature‐maps. …”
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MSIM: A Multiscale Iteration Method for Aerial Image and Satellite Image Registration by Xiaojia Liu, Yalin Ding, Chongyang Liu

“…Firstly, an image pyramid is established, and feature points are extracted based on phase congruency. …”
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Enhancing distant low-resource neural machine translation with semantic pivot by Enchang Zhu, Yuxin Huang, Yantuan Xian, Junguo Zhu, Minghu Gao, Zhiqiang Yu

“…Here, we propose a novel approach for incorporating similar linguistic features between Thai and Lao into the Chinese-Lao translation model. …”
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Research on multi-branch residual connection spectrum image classification based on attention mechanism by Zhong Xiaohui, Dong Sheng, Zhang Yiyi, Lu Wei, Jiang Lincen

“…In order to optimize this problem, this paper proposes a multi-branch residual-connected Efficient Global Attention (EGA) acoustic spectral image classification network based on the attention mechanism, which firstly separates the components with their respective acoustic features from the spectral noise, so as to achieve the purpose of noise reduction, and then extracts the Phase Resolved Partial Discharge (PRPD) Spectrum of the Intermediate Frequency (IF) cycle for the original signals that have undergone noise reduction, which is based on the attention mechanism through the Improved Global Attention Mechanism (IGAM) in the EGA of the backbone network. mechanism pays more attention to the channel and spatial features of the spectrogram, then improves the feature extraction ability by residual connection, and finally performs feature fusion with the mask branch. …”
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Research on a Bone Stick Fragment Stitching Method Based on Improved Corner Detection by Jiahuan Liu, Huiqin Wang, Rui Liu, Ke Wang, Zhan Wang, Ting Wang

“…The stitching of bone stick fragments is of great significance for the inheritance of and research into the outstanding traditional culture of the Western Han Dynasty. Focused on the problem that the existing methods have a low bone stick fragment stitching success rate due to their complex edges, this paper proposes a bone stick fragment stitching method based on improved corner detection, which strengthens the features of broken edges and improves the success rate of stitching. …”
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Similarity and wavelet transform based data partitioning and parameter learning for fuzzy neural network by Pramoda Patro, Krishna Kumar, G. Suresh Kumar, Gandharba Swain

“…To solve this issue in this proposed system Bat optimization based feature selection is proposed for optimal selection of features from the available dataset. …”
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GaitPart‑based Cross‑view Gait Recognition Method by LIU Jianhu, LIU Xing, GU Miao, WANG Junzhu, ZHANG Hailong, DENG Hongxia

“…[Purposes] To address the problem of sharp decrease in recognition accuracy caused by covariate factors such as camera view or pedestrian occlusion in gait recognition, an improved feature enhancement GaitPart cross-view gait recognition method IFE-GaitPart (An Improved Feature Enhancement GaitPart) is proposed. …”
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A Hybrid K-Means++ and Particle Swarm Optimization Approach for Enhanced Document Clustering by Eisha Hassan, Fazila Malik, Qazi Waqas Khan, Nadeem Ahmad, Muhammad Sardaraz, Faten Khalid Karim, Hela Elmannai

“…Document Clustering has attracted the interest of many researchers who have created several solutions to this problem by combining different techniques, models, and algorithms. …”
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Improved YOLOv7-Tiny for the Detection of Common Rice Leaf Diseases in Smart Agriculture by Fuxu Guo, Jing Li, Xingcheng Liu, Sinuo Chen, Hongze Zhang, Yingli Cao, Songhong Wei

“…The MobileNetV3 lightweight network is introduced to replace the backbone network of YOLOv7-tiny, which reduces the size of the model parameters and improves the extraction capability of features of different sizes; the RCS-OSA is used to replace the original ELAN-1 module, which improves the extraction capability of interlayer features; the TSCODE detector head is designed to enhance the extraction capability of the model for small targets; and the MPDIoU loss function is used to improve the model’s convergence speed and effect. …”
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Enhancing FTIR Spectral Feature Construction for Aero-Engine Hot Jet Remote Sensing via Integrated Peak Refinement and Higher-Order Statistical Fusion by Zhenping Kang, Yurong Liao, Xinyan Yang, Zhaoming Li

“…It adopted an adaptive threshold for the initial coarse detection of peaks, enhanced the positioning accuracy through local gradient optimization, dynamically screened the local strongest peak according to intensity information, and resolved the problem of overlapping peak resolution via an intelligent merging strategy based on the physical characteristics of spectral lines, achieving high-precision and high-robustness peak feature extraction. …”
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Transforming Early Breast Cancer Detection: A Deep Learning Approach Using Convolutional Neural Networks and Advanced Classification Techniques by Arun Kumar Singh, Bireshwar Dass Mazumdar, Rohit Raja, Kamred Udham Singh, Ankit Kumar, Mohd Asif Shah

“…Abstract Breast cancer is a major global health problem, with the WHO estimating approximately 2.3 million new cases every year. …”
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A Feature Selection Method by using Chaotic Cuckoo Search Optimization Algorithm with Elitist Preservation and Uniform Mutation for Data Classification by Le Wang, Yuelin Gao, Jiahang Li, Xiaofeng Wang

“…Nowadays, the feature selection problem as an optimization problem can be solved with nature-inspired algorithm. …”
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EBDet: Ellipse Feature Encode and Balanced Decoupling Label Assignment for Arbitrary-Oriented Ship Detection in Optical Remote Sensing Images by Tianqi Zhao, Yunhan Sun, Jin Qian, Zheng Li, Yunxiao Gao, Zhikang Zhao, Yongcheng Wang

“…The dynamic decoupling label assignment (DDLA) strategy adaptively evaluates the sample space sensitivity, and mitigates the feature misalignment problem by decoupling positive samples in classification and regression. …”
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Research on Arc Fault Detection Based on Conditional Batch Normalization Convolutional Neural Network with Cost-Sensitive Multi-Feature Extraction by Xin Ning, Tianli Ding, Hongwei Zhu

“…Although existing studies have made progress in improving the accuracy of their detection, most methods have not proposed effective solutions that address the cost-sensitive problem of feature selection. Thus, a multi-feature method is proposed by combining time-domain, frequency-domain, energy, and spatial features, which are integrated into a CBN (conditional batch normalization) convolutional neural network for detection. …”
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A model of feature extraction for well logging data based on graph regularized non-negative matrix factorization with optimal estimation by Kehong Yuan, Youlin Shang, Haixiang Guo, Yongsheng Dong, Zhonghua Liu

“…To solve this problem, we propose a feature extraction method named graph regularized non-negative matrix factorization with optimal estimation (GNMF-OE) according to the characteristics of well logging data in this paper. …”
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