CIT-EmotionNet: convolution interactive transformer network for EEG emotion recognition by Wei Lu, Lingnan Xia, Tien Ping Tan, Hua Ma

“…Emotion recognition is a significant research problem in affective computing as it has a lot of potential areas of application. …”
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THE IMPACT OF SPECIFIC FUNCTIONING OF UKRANIAN IRON AND STEEL WORKS ON THE PROCESSES OF PERSONNEL DEVELOPMENT by Tatiana S. Shul'gina, Tatiana V. Kovalenko

“…To solve this problem the authors conducted clusterization of Ukrainian iron and steel works. …”
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MW-UNet: Multi-Scale Weighted Connection UNet for Identification and Classification of Non-Meteorological Clutter over Big Radar Data by Mengmeng Cui, Chen Zeng, Xiaolong Xu, Muhammad Bilal, Xiaoyu Xia

“…Additionally, the channel-focused feature fusion mechanism is able to analyze the deep latent features of the input parameters and suppress the useless features, so that only six polarization parameters are required as inputs. …”
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AE-XGBoost: A Novel Approach for Machine Tool Machining Size Prediction Combining XGBoost, AE and SHAP by Mu Gu, Shuimiao Kang, Zishuo Xu, Lin Lin, Zhihui Zhang

“…Grey correlation analysis (GRA) and principal component analysis (PCA) were used to reduce the dimensions of the original data features, and the synthetic minority overstimulation technique of the Gaussian noise regression (SMOGN) method was used to deal with the problem of data imbalance. …”
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DBN Classifier for Classification of Benign and Malignant Solitary Pulmonary Nodule by LIU Lu, YANG Pei-liang, SUN Wei-wei, ZHOU Yang, ZHAO Hong-yuan

“…Before this team work，768 dimensional feature space is obtained by multi-resolution histograms of SPN image． …”
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Research on dust identification and concentration detection method based on machine vision by Luyang TU, Qinghua CHEN, Yingsong CHENG, Bingyou JIANG

“…At the same time, the dust image in the dust concentration data set is transformed into different color spaces, and the color features and texture features are extracted. The relationship between these features and dust concentration is analyzed to establish a multivariate model. …”
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Hydraulic System Fault Diagnosis Based on Dual-Channel Convolutional Neural Network and Improved D-S Evidence Theory by Jiyang Qi, Yue Qi, Shenghua Luo, Jiahao Zhang

“…To address the problem that the traditional convolutional neural network (CNN) cannot fully extract the fault feature information in a single channel and the accuracy of hydraulic system fault diagnosis based on a single signal is not high, a fault diagnosis method combining dual-channel CNN and improved D-S evidence theory is proposed. …”
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A Novel Multi-Task and Ensembled Optimized Parallel Convolutional Autoencoder and Transformer for Speech Emotion Recognition by Zahra Sharifzadeh Jafari, Sanaz Seyedin

“…The PCAEs have been proposed to generate high-level informative harmonic sparse features from the input. With the aid of the proposed parallel CAE, we can extract nonlinear sparse features in an ensemble manner improving the accuracy and the generalization of the model. …”
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Forensic economic examination in the investigation of corruption crimes by L. A. Parfentii

“…However, the procedure for conducting forensic economic expertise in Ukraine is not without drawbacks, and when carried out within the framework of the investigation of specific corruption crimes is characterized by certain features. The purpose of the article is to generalize and systematize key features, as well as to identify weaknesses in the process of forensic economic examination in the investigation of corruption crimes in Ukraine. …”
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ACA-Net: adaptive context-aware network for basketball action recognition by Yaolei Zhang, Fei Zhang, Yuanli Zhou, Xiao Xu

“…The LSTA module adaptively learns global and local temporal features of the video. The TSCI module enhances the feature representation by learning the interaction features between space and channels. …”
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Synthesis of an Algorithm for Classifying Underwater Objects on Based on the Analysis of their Noise Spectra by Evgeniy Storozhok, Vladimir Kristalinskii

“…The paper describes the development of an algorithm for the recognition and classification of hydroacoustic noises of technogenic and biological origin through the use of significant spectral features. The solution of the problem of classification of underwater objects is based on the use of the mathematical apparatus of the theory of fuzzy sets. …”
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Cross-Modal Data Fusion via Vision-Language Model for Crop Disease Recognition by Wenjie Liu, Guoqing Wu, Han Wang, Fuji Ren

“…While most existing deep learning-based methods focus primarily on image datasets for disease recognition, they often overlook the complementary role of textual features in enhancing visual understanding. To address this problem, we proposed a cross-modal data fusion via a vision-language model for crop disease recognition. …”
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Improved printed circuit board defect detection scheme by Lufeng Bai, Wen Hao Xu

“…In addition, we draw on the advanced BiFPN structure, which enables the bidirectional flow of feature information between multiple layers and greatly improves the capture and integration of small target features. …”
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YOLO-WAD for Small-Defect Detection Boost in Photovoltaic Modules by Yin Wang, Wang Yun, Gang Xie, Zhicheng Zhao

“…Subsequently, an additional detection layer is added to the neck, and C2f is replaced by C2f-EMA (CSP bottleneck with two convolutions–efficient multi-scale attention mechanism), which can redistribute feature weights and prioritize relevant features and spatial details across image channels to improve feature extraction. …”
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DESIGNING THE NATIONAL PAST IN THE ESSAYISTIC PRACTICE OF THE HISTORY WRITING OF CATHERINE THE GREAT AND I. P. ELAGIN by S. Malovichko

“…The studyactualizes the problem of classifying historiographical sources of the second half of the 18th century, in particular of their kind as an essay ("ocherk" - in rus., AbriGVUmrilJ" - in germ.). …”
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A novel pansharpening method based on cross stage partial network and transformer by Yingxia Chen, Huiqi Liu, Faming Fang

“…Abstract In remote sensing image fusion, the conventional Convolutional Neural Networks (CNNs) extract local features of the image through layered convolution, which is limited by the receptive field and struggles to capture global features. …”
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Deep structure of South Kamchatka according to geophysical data by Yu. F. Moroz, L. I. Gontovaya

“…Comprehensive analysis of the geological and geophysical data shows differences in the structure of the crust and upper mantle in North and South Kamchatka and common features of the deep structures of South Kamchatka and the Kuril Islands. …”
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Using the TSA-LSTM two-stage model to predict cancer incidence and mortality. by Rabnawaz Khan, Wang Jie

“…By commencing with input feature attention, this model attention technique guarantees that the model encoder converges to a subset of input sequence features during the prediction of output sequence features. …”
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Escalation as a way to resolve conflicts and contradictions by J. G. Evdokimova, S. M. Sycheva, T. B. Shramchenko, E. A. Khalimon

“…The psychological features of the conflict escalation are analysed, which are manifested in the reluctance of domestic leaders to take the problem higher because of the fear of not being able to cope with the management of the conflict. …”
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Video description method based on multidimensional and multimodal information by Enjie DING, Zhongyu LIU, Yafeng LIU, Wanli YU

“…In order to solve the problem of complex information representation in automatic video description tasks,a multi-dimensional and multi-modal visual feature extraction and fusion method was proposed.Firstly,multi-dimensional features such as static and dynamic attributes of the video sequence were extracted by transfer learning,and the image description algorithm was also used to extract the semantic information of the key frames in the video.By doing this,the video features extraction was carried out.Then,multi-layer long and short memory networks were used to fuse multi-dimensional and multi-modal information,and finally generated a language description of the video content.Compared with the existing methods,experimental simulations results show that the proposed method achieves better results in the video automatic description task.…”
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