Classification of Metro Facilities with Deep Neural Networks by Deqiang He, Zhou Jiang, Jiyong Chen, Jianren Liu, Jian Miao, Abid Shah

“…Intelligent monitoring systems based on computer vision not only complete safeguarding tasks efficiently but also save a great deal of human labor. Deep convolutional neural networks (DCNNs) are the most state-of-the-art technology in computer vision tasks. …”
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FD²-YOLO: A Frequency-Domain Dual-Stream Network Based on YOLO for Crack Detection by Junwen Zhu, Jinbao Sheng, Qian Cai

“…Furthermore, the Dynamic Inter-Domain Feature Fusion module (DIFF) is introduced, which uses large-kernel deep convolution and Hadamard to enable the adaptive fusion of features from different domains, thus addressing the problem of difficult feature fusion due to domain differences. …”
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Analysis of communities and groups in social networks as a significant factor of influence on cryptocurrency rates by Olena Gavrilenko, Mykhailo Myagkyi

“… Currently, most existing cryptocurrency exchanges do not have tools in their arsenal that would allow them to verify and investigate information disseminated on social media regarding a particular cryptocurrency. …”
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Student academic performance prediction via hypergraph and TabNet by Yisheng Yang, Shiyu Zhao, Sufang An, Xiaoyong Li, Yong Zhang

“…However, existing methods mostly focus on modeling individual student behaviors, neglecting the complex associations among students hidden within campus behavioral data. …”
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Efficient detection of highway pavement cracks using computer vision-based MSFNet model by Zhengfa Jiang, Danlan Li, Ting Zhao, Mingxing Gao

“…Most highway pavement cracks are long and thin with rich edge details. …”
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STDNet: Improved lip reading via short-term temporal dependency modeling by Xiaoer Wu, Zhenhua Tan, Ziwei Cheng, Yuran Ru

“…Deep-learning-based lip reading has greatly improved performance in current datasets; however, most existing research ignores the significance of short-term temporal dependencies of lip-shape variations between adjacent frames, which leaves space for further improvement in feature extraction. …”
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SegPhase: development of arrival time picking models for Japan’s seismic network using the hierarchical vision transformer by Shinya Katoh, Yoshihisa Iio, Hiromichi Nagao, Hiroshi Katao, Masayo Sawada, Kazuhide Tomisaka

“…In contrast to conventional convolution-based models, SegPhase employs a hierarchical vision transformer structure that utilizes multi-head self-attention to dynamically focus on important waveform features, such as P- and S-wave onsets, noise, and coda waves. …”
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Polarization of road target detection under complex weather conditions by Feng Huang, Junlong Zheng, Xiancai Liu, Ying Shen, Jinsheng Chen

“…This module integrates channel-wise global self-attention and small kernel convolution to adaptively adjust the polarization enhancement method using dynamically extracted global and local polarization feature information. …”
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A Random Degradation Aggregation Network With Temporal-Spatial Attention for Satellite Video Super-Resolution by Lu Li, Mi Wang, Yingdong Pi

“…Finally, we introduce an optical flow-guided deformable convolution module for aligning sequential frames, integrated with a temporal-spatial attention mechanism to effectively fuse temporal and spatial features. …”
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A Multiscale Mixed-Graph Neural Network Based on Kinematic and Dynamic Joint Features for Human Motion Prediction by Rongyong Zhao, Bingyu Wei, Lingchen Han, Yuxin Cai, Yunlong Ma, Cuiling Li

“…Kinematic features, including joint coordinates and velocity, are commonly employed in skeleton-based human motion prediction. Nevertheless, most existing approaches neglect the critical role of dynamic information and tend to degrade as the prediction length increases. …”
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LGM-Net: Wheat Pest and Disease Detection Network Based on Local Global Information Interaction and Multi-Level Feature Fusion by Yimin Qu, Shaobo Yu, Jing Yang

“…Wheat, as one of the most critical and widely consumed crops globally, is of irreplaceable importance to the food supply and agricultural economy. …”
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GES-YOLO: A Light-Weight and Efficient Method for Conveyor Belt Deviation Detection in Mining Environments by Hongwei Wang, Ziming Kou, Yandong Wang

“…Specifically, to improve real-time detection capabilities, we introduce the Groupwise Separable Convolution (GSConv) module. Additionally, by analyzing scene features, we remove the large object detection layer, which enhances the detection speed while maintaining the feature extraction capability. …”
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SKIN RASH CLASSIFICATION SYSTEM USING MODIFIED DENSENET201 THROUGH RANDOM SEARCH FOR HYPERPARAMETER TUNING by Fayza Nayla Riyana Putri, R.Rizal Isnanto, Aris Sugiharto

“…The findings highlight the potential of Random Search for hyperparameter tuning to enhance the performance of deep convolutional neural networks in the medical image classification domain, offering a promising tool for efficient and accurate skin disease detection. …”
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Classification of lung cancer severity using gene expression data based on deep learning by Ali Bou Nassif, Nour Ayman Abujabal, Aya Alchikh Omar

“…Abstract Lung cancer is one of the most prevalent diseases affecting people and is a main factor in the rising death rate. …”
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Anomaly-Guided Double Autoencoders for Hyperspectral Unmixing by Hongyi Liu, Chenyang Zhang, Jianing Huang, Zhihui Wei

“…Deep learning has emerged as a prevalent approach for hyperspectral unmixing. However, most existing unmixing methods employ a single network, resulting in moderate estimation errors and less meaningful endmembers and abundances. …”
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Indoor Positioning Systems in Logistics: A Review by Laura Vaccari, Antonio Maria Coruzzolo, Francesco Lolli, Miguel Afonso Sellitto

“…Geometric methods, particularly multilateration, proved to be the most effective for positioning and are supported by advanced filtering techniques like the Extended Kalman Filter and machine learning models such as Convolutional Neural Networks. …”
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A Multi-Branch Attention Fusion Method for Semantic Segmentation of Remote Sensing Images by Kaibo Li, Zhenping Qiang, Hong Lin, Xiaorui Wang

“…However, due to the inherent complexity of remote sensing images, most attention mechanisms designed for natural images underperform when applied to remote sensing data. …”
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Computer-Aided Diagnosis Techniques for Brain Tumor Segmentation and Classification Using MRI by Gadicha A. B., Kale Prachi V., Dalvi G. D., Mohod M. M., Pakhale S. C., Khan S. M.

“…Brain tumors are among the most life-threatening neurological conditions, characterized by the abnormal and uncontrolled growth of brain cells. …”
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Deep FS: A Deep Learning Approach for Surface Solar Radiation by Fatih Kihtir, Kasim Oztoprak

“…The method extracted and provided the selected features that are most appropriate for predicting the surface exposure. …”
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Modelling on Car-Sharing Serial Prediction Based on Machine Learning and Deep Learning by Nihad Brahimi, Huaping Zhang, Lin Dai, Jianzi Zhang

“…Meanwhile, the model using all the different feature categories results in the most precise prediction than any of the models using one feature category at a time…”
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