An Innovative Neighbor Attention Mechanism Based on Coordinates for the Recognition of Facial Expressions by Cheng Peng, Bohao Li, Kun Zou, Bowen Zhang, Genan Dai, Ah Chung Tsoi

“…For solving the facial expression recognition (FER) problem, we introduce a novel feature extractor called the coordinate-based neighborhood attention mechanism (CNAM), which uses the coordinate attention (CA) method to capture the directional relationships in separate horizontal and vertical directions, the input features from a preprocessing unit, and then passes this to two residual blocks, one consisting of the neighborhood attention (NA) mechanism, which captures the local interaction of features within the neighborhood of a feature vector, while the other one contains a channel attention implemented by a multilayer perceptron (MLP). …”
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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…Secondly, a new neck network structure BCFPN (Bidirectional Collocated Feature Pyramid Network) is designed based on the weighted bidirectional feature pyramid network, which enhances the feature fusion and the interaction of contextual information, and improves the detection accuracy of the model. …”
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ENDNet: Extra-Node Decision Network for Subgraph Matching by Masaki Shirotani, Motoki Amagasaki, Masato Kiyama

“…Specifically, GNNs generate new node features by aggregating information from adjacent nodes, meaning that even if nodes in the query and data graphs start with identical features, the presence of extraneous nodes or edges in the data graph can distort feature representations and hinder accurate matching. …”
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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

“…Although hyperspectral image classification methods based on convolutional neural networks (CNN) have noticeably improved performance, there are still certain shortcomings in the extraction of detailed and local features. Therefore, how to fully utilize spatial and spectral information in situations with limited samples has become a challenging problem. …”
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Real-Time Image Semantic Segmentation Based on Improved DeepLabv3+ Network by Peibo Li, Jiangwu Zhou, Xiaohua Xu

“…First, the MobileNetV2 model with less computational overhead and number of parameters is selected as the backbone network to improve the segmentation speed; then, the Feature Enhancement Module (FEM) is introduced to several shallow features with different scale sizes in MobileNetV2, and then these shallow features are fused to improve the utilization rate of the model encoder on the edge information, to retain more detailed information and to improve the network’s feature representation ability for complex scenes; finally, to address the problem that the output feature maps of Atrous Spatial Pyramid Pooling (ASPP) module do not pay enough attention to detailed information after merging, the FEM attention mechanism is introduced on the feature maps processed by the ASPP module. …”
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Multi-scale ship detection algorithm in SAR images in complex scenes by He Shun, Wang Yuzhu, Yang Zhiwei

“…Firstly, a multi-scale object feature extraction network (MFE-Net) is used to extract feature information to improve the detection capability of multi-scale objects and reduce redundant calculations. …”
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Research on Target-detection and Tracking of Intelligent Mine Trucks in Open-pit Mines by LI Yuanzhengyu, HU Yunqing, LONG Teng, HUANG Wenyu, PAN Wenbo, LI Peijie

“…Among them, feature extraction module uses point cloud gradient and distance feature extraction methods to solve the point cloud segmentation problem of small and irregular-shaped obstacles in changing scenes; target tracking module constructs track information for multi-target tracking, which improves the stability of target tracking; an asynchronous fusion strategy of multi-source sensors is designed for heterogeneous sensor fusion module, which overcomes the problem of heterogeneous sensor fusion, and improves the detection and tracking capabilities of small and various targets in unpaved road and dusty environment of open-pit mines. …”
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Influence of Sliding Time Window Size Selection Based on Heart Rate Variability Signal Analysis on Intelligent Monitoring of Noxious Stimulation under Anesthesia by Qiang Yin, Dai Shen, Qian Ding

“…Some researches based on medical signals have failed to provide a general understanding of this problem. This paper presents a feature extraction method for heart rate variability signals, aiming at further improving the evaluation of noxious stimulation. …”
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Research on bearing fault diagnosis of reciprocating compressors based on GMDE and MFO-MKELM algorithms by LI Yanyang, WANG Jindong, NING Liuyang, MA Lei

“…ObjectiveAiming at the problem that the bearing fault feature extraction is difficult and the recognition accuracy is not high due to the characteristics of local strong non-stationarity and nonlinearity of the vibration signal of reciprocating compressor bearing clearance, a new method based on GMDE and MFO-MKELM algorithm was proposed.MethodsFirst, spread on multiscale entropy in the process of coarse graining, the average coarse graining way to a certain extent, “neutralize” the dynamics of the original signal mutation behavior, and reduce the accuracy of the entropy analysis. …”
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Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM by Ya jie Li, Shao bing Li, Wei Li

“…First, the feature sets of 11 kinds of monitoring data are optimized and selected based on MIC for self-powered power supply system. …”
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Remaining Useful Life Prediction for Rolling Bearings Based on TCN–Transformer Networks Using Vibration Signals by Xiaochao Jin, Yaping Ji, Shiteng Li, Kailang Lv, Jianzheng Xu, Haonan Jiang, Shengnan Fu

“…In addition, a new RUL prediction method, TCN–Transformer, is developed which can efficiently learn and integrate local and global features of vibration signals, addressing the long time series prediction problem in RUL prediction. …”
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Multiscale Task-Decoupled Oriented SAR Ship Detection Network Based on Size-Aware Balanced Strategy by Shun He, Ruirui Yuan, Zhiwei Yang, Jiaxue Liu

“…Therefore, to address the issues of scale diversity, intra-class imbalance in ship data, and the feature conflict problem associated with traditional coupled detection heads, we propose an SAR image multiscale task-decoupled oriented ship target detector based on a size-aware balanced strategy. …”
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ShipYOLO: An Enhanced Model for Ship Detection by Xu Han, Lining Zhao, Yue Ning, Jingfeng Hu

“…In the training process, the 3 × 3 convolution, 1 × 1 convolution, and identity parallel mode are used to replace the original feature extraction component (ResUnit) and more features are extracted. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

“…Problems such as a difficulty in feature selection and poor generalization ability were prone to occur when traditional method was exploited to detect abnormal network traffic.Therefore, an abnormal traffic detection method based on the long short term memory network (LSTM) and improved residual neural network optimization was proposed.Firstly, the features and attributes of network traffic were analyzed, and the variability of the feature values was reduced by preprocessing of network traffic.Then, a three-layer stacked LSTM network was designed to extract network traffic features of different depths.Moreover, the problem of weak adaptability of feature extraction was solved.Finally, an improved residual neural network with skipping connecting line was designed to optimize the LSTM.The defects of deep neural network such as overfitting and gradient vanishing were optimized.The accuracy of abnormal traffic detection was improved.Experimental results show that the proposed method has higher training accuracy and better visibility of data processing.The classification accuracy rates under two classifications and multiple classifications are 92.3% and 89.3%.It has the lowest false positive rate when the parameters such as precision rate and recall rate are optimal.Moreover, it has strong robustness when the sample is destroyed.Furthermore, better generalization ability can be achieved.…”
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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…The multi-source data fusion algorithm should not only have the ability of intelligent feature extraction and related analysis, but also deal with the uncertainty and redundancy of data to adapt to the dynamic needs of urban development. …”
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Improving company communication activity amidst the СOVID-19 restrictions by Volodymyr Kyslyy, Tetyana Bondar, Yevhen Kabluchko, Hlib Lieonov

“…Besides, the SWOT analysis was conducted to disclose the company organization's activities features. The authors examined the company's competitive environment using the 4P concept, which allowed identifying the company's main advantages and searches for solutions to existing problems in the communication activities. …”
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Conceptualizing the Public Component of Green Finance by Horyn Volodymyr P., Sydor Iryna P., Bula Pavlo V., Mudryi Taras P.

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GANs for data augmentation with stacked CNN models and XAI for interpretable maize yield prediction by Ishaan Seshukumar Pothapragada, Sujatha R

“…A robust maize yield prediction framework is proposed to counter major problems predominantly present in Agri-tech analytics, like scarcity of data, class imbalance, redundant features, and model interpretability. …”
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DeepMoIC: multi-omics data integration via deep graph convolutional networks for cancer subtype classification by Jiecheng Wu, Zhaoliang Chen, Shunxin Xiao, Genggeng Liu, Wenjie Wu, Shiping Wang

“…Conclusion The introduction of Deep GCN shows encouraging performance in terms of supervised multi-omics feature learning, offering promising insights for precision medicine in cancer research. …”
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The India's foreign policy at the present stage: main landmarks by M. M. Abazalieva, M. G. Pavlova

“…The research is conducted through consideration of such problems as maintaining the system of national interests of a given state, where, as in most countries of the world, security occupies a central place. …”
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