MSAM：Video Question Answering Based on Multi-Stage Attention Model by LIANG Li-li, LIU Xin-yu, SUN Guang-lu, ZHU Su-xia

“…This network extracts multi-modal features such as video, audio and text and feeds these features into the multi-stage attention model (MSAM), which is able to accurately locate the video information through a stage-by-stage localization method.In order to improve the effectiveness of feature fusion, a triplemodal compact concat bilinear (TCCB) algorithm is proposed to calculate the correlation between different modal features.This network is tested on the ZJL dataset.The average accuracy rate is 54.3%, which is nearly 15% higher than the traditional method and nearly 7% higher than the exist method.…”
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A BEARING DEEP LEARNING TRANSFER DIAGNOSIS METHOD BASED ON OPTIMIZATION OF SYMMETRIC POLAR COORDINATES by WU DingHai, WANG HuaiGuang, SONG Bin, ZHANG YunQiang

“…Aiming at the problem of graphical feature representation of one-dimensional mechanical vibration signals, a bearing fault diagnosis method based on symmetric polar coordinates and residual network migration learning is proposed, which combines the powerful image classification and recognition ability of convolution neural network. …”
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DYNAMIC THRESHOLD CALCULATION METHOD FOR BEARING OF HELICOPTER SWASHPLATE BASED ON BAYESIAN INFERENCE by CONG Lei, XIONG BangShu, LI Xin Min, SUN Wei, JIN XiaoQiang

“…Firstly,the singular value decomposition was used to preprocess the vibration signal,and the influence of noise on the dynamic threshold calculation result was filtered out.Secondly,the fault frequency energy feature extracting method was used to extract the features of normal data and inner ring,outer ring and ball fault data. …”
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Improvement of the classification of intangible assets for accounting purposes by S.E. Pyrizhok, E.G. Melnik

“…The article deals with the problem issues of the classification of intangible assets for the accounting and analytical maintenance of operations with them. …”
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DOE: a dynamic object elimination scheme based on geometric and semantic constraints by Yanli Liu, Siyi Chen, Heng Zhang, Neal N. Xiong, Wei Liang

“…In this paper, we propose a dynamic object elimination algorithm that combines semantic and geometric constraints to address the problem of visual SLAM being easily affected by dynamic feature points in dynamic environments. …”
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Manet: motion-aware network for video action recognition by Xiaoyang Li, Wenzhu Yang, Kanglin Wang, Tiebiao Wang, Chen Zhang

“…Actions in videos may vary at different speeds or scales, and it is difficult to cope with a wide variety of actions by relying on a single spatio-temporal scale to extract features. To address this problem, we propose a Motion-Aware Network (MANet), which includes three key modules: (1) Local Motion Encoding Module (LMEM) for capturing local motion features, (2) Spatio-Temporal Excitation Module (STEM) for extracting multi-granular motion information, and (3) Multiple Temporal Aggregation Module (MTAM) for modeling multi-scale temporal information. …”
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ID-insensitive deepfake detection model based on multi-attention mechanism by Yuncan Sheng, Zhengrui Zou, Zongxuan Yu, Mengxue Pang, Wei Ou, Wenbao Han

“…However, existing methods frequently overlook the connection between local details and overall image features, while also failing to address the problem of implicit identity leakage. …”
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A YOLO-Based Method for Head Detection in Complex Scenes by Ming Xie, Xiaobing Yang, Boxu Li, Yingjie Fan

“…Secondly, it was found in practical operations that the original IoU function has a serious problem with overlapping detection in complex scenes. …”
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SERNet: Spatially Enhanced Recalibration Network for Building Extraction in Dense Remote Sensing Scenes by Kuikui Han, Yuanwei Yang, Xianjun Gao, Dongjie Yang, Lei Xu

“…In the first stage, the designed parallel path feature extraction architecture is used to acquire deep semantic features by the spatial path to retain spatial information and contextual path to acquire deep semantic features. …”
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Small target detection in coal mine underground based on improved RTDETR algorithm by Feng Tian, Cong Song, Xiaopei Liu

“…By introducing Deformable Attention in the coding part of the RTDETR algorithm, the deformable feature of this attention mechanism is used to improve the network’s ability to extract effective image features. …”
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A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT by Wei Huang, Qifeng Yan, Lei Mou, Yitian Zhao, Wei Chen, Wei Chen, Wei Chen

“…To address the problem of low contrast and blurred boundaries of choroidal vessels in OCT images, we developed a large kernel and multi-scale attention module, which can improve the features of the target area through multi-scale convolution kernels, channel mixing and feature refinement. …”
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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). …”
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Machine Learning Models for Tracking Blood Loss and Resuscitation in a Hemorrhagic Shock Swine Injury Model by Jose M. Gonzalez, Ryan Ortiz, Lawrence Holland, Austin Ruiz, Evan Ross, Eric J. Snider

“…Hemorrhage leading to life-threatening shock is a common and critical problem in both civilian and military medicine. Due to complex physiological compensatory mechanisms, traditional vital signs may fail to detect patients’ impending hemorrhagic shock in a timely manner when life-saving interventions are still viable. …”
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DepthRL: a weakly supervised approach for monocular depth estimation using deep reinforcement learning by Han Chen, Yongxiong Wang, Jiayi Zhang, Jiapeng Zhang, Zhiqun Pan, Shuwen Jia, Shuai Huang

“…In this network, we introduce the Multiscale Cross Attention Feature Enhancement Module (MCFEM), which enhances the upward transfer of low-order features, allowing high-level semantics to be complemented by low-level local details. …”
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Clothes Retrieval Using M-AlexNet With Mish Function and Feature Selection Using Joint Shannon’s Entropy Pearson’s Correlation Coefficient by Marryam Murtaza, Muhammad Sharif, Mussarat Yasmin, Muhammad Fayyaz, Seifedine Kadry, Mi Young Lee

“…However, significant clothes image variations degrade visual search retrieval accuracy. Another problem with retrieval accuracy is the high dimensions of feature vectors obtained from pre-trained deep CNN models. …”
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Tomato ripeness detection and fruit segmentation based on instance segmentation by Jinfan Wei, Yu Sun, Yu Sun, Lan Luo, Lingyun Ni, Mengchao Chen, Minghui You, Minghui You, Ye Mu, Ye Mu, He Gong, He Gong

“…By deformable convolution and multi-directional asymmetric convolution, the AOFRM module adaptively extracts the shape and direction features of tomatoes to solve the problems of occlusion and overlap. …”
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THE INTERACTION OF REGIONAL ECONOMIES OF RUSSIA by Z. Musaeva

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Report on the 4th International Conference of PhD Students and Young Researchers ‘Faces of Guitar in Scientific Research’, Jan Długosz University in Częstochowa, 17 April 2024... by Miłosz MĄCZYŃSKI

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UKRAINIAN ENTREPRENEURSHIP IN POLAND: CHALLENGES AND OPPORTUNITIES by Valentyna Smachylo, Olha Rudachenko, Oleh Kulinich, Dmytro Simonov

“…The article is devoted to solving the problem of developing Ukrainian business projects in the Polish market. …”
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EPIDEMIOLOGICAL FEATURES OF NON-ALCOHOLIC FATTY LIVER DISEASE IN NOVOSIBIRSK (SIBERIAN FEDERAL DISTRICT): REGIONAL DATA OF OPEN MULTICENTER PROSPECTIVE STUDY DIREG 2 by V. V. Tsukanov, A. S. Yurkina, T. A. Ushakova, D. V. Blinov

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