Oxide Phototransistor Array With Multiply-and-Accumulation Functions for In-Sensor Image Processing by Saisai Wang, Xiaotao Jing, Wanlin Zhang, Rui Wang, Hong Wang, Qi Huang

“…Advanced in-sensor computing paradigm has gradually become a research hotspot in this IOT era of sensor data proliferation. However, most existing in-sensor computing devices are plagued by a complex structure, and the uniformity of the sensor array is difficult to ensure. …”
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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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Multi-Feature Fusion for Enhanced Feature Representation in Automatic Modulation Recognition by Jiuxiao Cao, Rui Zhu, Lingfeng Wu, Jun Wang, Guohao Shi, Peng Chu, Kang Zhao

“…With the advancement of deep learning, automatic modulation recognition has emerged as a promising solution. Nonetheless, most existing deep learning-based modulation recognition studies consider only single-domain feature information of the signal, such as time-domain or frequency-domain features. …”
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Analysis of Time-Fractional Delay Partial Differential Equations Using a Local Radial Basis Function Method by Kamran, Kalsoom Athar, Zareen A. Khan, Salma Haque, Nabil Mlaiki

“…The Laplace transform, which is one of the most powerful techniques for solving integer- and non-integer-order problems, is used to represent the desired solution as a contour integral in the complex plane, known as the Bromwich integral. …”
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Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…SHAP feature analysis reveals that the control conductor features have the most substantial influence on predictions, with a SHAP value of 0.095. …”
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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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Underground helmet detection algorithm based on improved YOLOv8s by Jiaru YANG, Yinan QIN, Tianxu LI, Han ZHUANG

“…In the process of coal mine underground operation, the safety helmet is the most direct and effective protective measure, and it is an important measure to ensure the safety of miners. …”
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Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation by Xianzhi Deng, Xiaolong Hu, Liangsheng Shi, Chenye Su, Jinmin Li, Shuai Du, Shenji Li

“…The photosynthesis-sensitive spectral bands identified by our model were predominantly in the visible range. The most sensitive vegetation indices form discovered by our model was Reflectancenear−infrared+Reflectancegreen/blueReflectancenear−infrared×Reflectancered. …”
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Efficient Single-Exposure Holographic Imaging via a Lightweight Distilled Strategy by Jiaosheng Li, Haoran Liu, Zeyu Lai, Yifei Chen, Chun Shan, Shuting Zhang, Youyou Liu, Tude Huang, Qilin Ma, Qinnan Zhang

“…The integration of deep learning (DL) advancements with physics-informed methodologies has opened new avenues for tackling this challenge. However, most of the existing DL-based holographic reconstruction methods have high model complexity. …”
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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

“…Compared to PhaseNet, the most widely used deep learning model, SegPhase improved arrival time match rates by ~ 11% and detected ~ 15% more events in continuous waveform tests, particularly enhancing the detection of small-magnitude events. …”
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Polarization of road target detection under complex weather conditions by Feng Huang, Junlong Zheng, Xiancai Liu, Ying Shen, Jinsheng Chen

“…The optimal polarization parameters should be adaptively adjusted to weather conditions, angles and target features, whereas most existing research employs handcrafted polarization parameters without considering actual complex detection requirements, which are unable to adaptively adjust the polarization feature enhancement methods. …”
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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

“…In recent years, video super-resolution (VSR) has achieved significant progress. However, most existing VSR methods rely on fixed and known degradation models, such as bicubic downsampling, which limits their effectiveness in real-world scenarios characterized by diverse and unknown degradations. …”
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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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MFFSNet: A Lightweight Multi-Scale Shuffle CNN Network for Wheat Disease Identification in Complex Contexts by Mingjin Xie, Jiening Wu, Jie Sun, Lei Xiao, Zhenqi Liu, Rui Yuan, Shukai Duan, Lidan Wang

“…Wheat is one of the most essential food crops globally, but diseases significantly threaten its yield and quality, resulting in considerable economic losses. …”
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Testing a New Star Formation History Model from Principal Component Analysis to Facilitate Spectral Synthesis Modeling by Yanzhe Zhang, H. J. Mo, Katherine E. Whitaker, Shuang Zhou

“…The spectrum of a galaxy is a complicated convolution of many properties of the galaxy, such as the star formation history (SFH), initial mass function, and metallicity. …”
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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

“…Conveyor belt deviation is one of the most common failures in belt conveyors. To address issues such as the high computational complexity, large number of parameters, long inference time, and difficulty in feature extraction of existing conveyor belt deviation detection models, we propose a GES-YOLO algorithm for detecting deviation in mining belt conveyors, based on an improved YOLOv8s model. …”
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Siamese text classification network (SiamTCN) for multi-class multi-label information extraction of typhoon disasters from social media data by Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou, Xueqiang Zhao

“…Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster research. However, most existing classification methods for typhoon disasters are limited to multi-class but single-label levels, contradicting the reality that a social media text may correspond to multiple types of disaster damage. …”
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