GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…The Dilated Encoder network is introduced to cover different-scale targets by differentiating receptive fields, and the feature weight allocation is optimized by combining it with a Convolutional Block Attention Module (CBAM). …”
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Pollen detection through integrated microfluidics and smartphone-driven deep learning systems by Kang Chen, Xi Chen, Guodong Sui

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Understanding the ancient classic and famous prescriptions via the property of Chinese materia medica by Dan Qin, Dan Qin, He Zhang, Bin Du, Hui Wang, Ligang Liu, Yun Wang

“…We formulated the backward process as a constrained combinatorial optimization problem to rebuild ACFPs from their PCCMMs. …”
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Impact of new coalbed methane wells on old well productivity and its controlling factors: a case study of Shizhuangnan block in Qinshui Basin by Xueting HAN, Shangzhi MENG, Guangjing LIU, Zhenyu REN, Shu TAO, Xinyang MEN, Ziyang WEI

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A time series algorithm to predict surgery in neonatal necrotizing enterocolitis by Cheng Cui, Ling Qiu, Ling Li, Fei-Long Chen, Xiao Liu, Huan Sun, Xiao-Chen Liu, Lei Bao, Lu-Quan Li

“…Abstract Background Determining the optimal timing of surgical intervention for Neonatal necrotizing enterocolitis (NEC) poses significant challenges. …”
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Short-Term Load Forecasting Based on Similar Day Theory and BWO-VMD by Qi Cheng, Jing Shi, Siwei Cheng

“…The high-frequency component is predicted using the similar day averaging method, while neural networks are employed for the medium and low-frequency components, leveraging historical and similar-day data, respectively. …”
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Pipe roughness calibration in oil field water injection system by Yuxue Wang, Songyu Bai

“…The interior-point method was employed to solve this problem, yielding a global optimal solution. Simulation results on an actual network showed that the proposed method reduced the average error of the roughness coefficient by 4.9%, from 7.08% to 2.18%, demonstrating its effectiveness.…”
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Underwater Sound Speed Profile Inversion Based on Res-SACNN from Different Spatiotemporal Dimensions by Jiru Wang, Fangze Xu, Yuyao Liu, Yu Chen, Shu Liu

“…The optimization ratio hits 71.8% and the average RMSE decreases by 7.39 m/s in the six-region experiment. …”
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Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches by Nadenlla RajamohanReddy, G. Muneeswari

“…Conditional Tabular Generative Adversarial Network (CTGAN) is used to tackle class imbalance problems. …”
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Enhancing Deep Learning Sustainability by Synchronized Multi Augmentation with Rotations and Multi-Backbone Architectures by Nikita Gordienko, Yuri Gordienko, Sergii Stirenko

“…The outputs provided by these MBs are merged through different fusion strategies: Averaging Fusion with aggregation of predictions and Dense Fusion with integration of features via a fully connected neural network. …”
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Early prediction of proton therapy dose distributions and DVHs for hepatocellular carcinoma using contour-based CNN models from diagnostic CT and MRI by Toshiya Rachi, Taku Tochinai

“…Gamma passing rates averaged 82–83% for IMPT and 92–93% for passive techniques. …”
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Advanced ENF Region Classification Using UniTS-SinSpec: A Novel Approach Integrating Sinusoidal Activation Function and Spectral Attention by Yujin Li, Tianliang Lu, Gaojun Zeng, Kai Zhao, Shufan Peng

“…Training is conducted using a public dataset on the open science framework (OSF) platform, with final experimental results demonstrating that, after parameter optimization, the UniTS-SinSpec model achieves an average validation accuracy of 97.47%, surpassing current state-of-the-art and baseline models. …”
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Visual Point Cloud Map Construction and Matching Localization for Autonomous Vehicle by Shuchen Xu, Kedong Zhao, Yongrong Sun, Xiyu Fu, Kang Luo

“…We fuse multi-source information from vehicle-mounted sensors and the regional road network to establish the geographically high-precision VPCM. …”
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Channel equalization in ultraviolet communication based on LSTM-DNN hybrid model by Liwei Zhang

“…This study proposes a Long Short-Term Memory - Deep Neural Network (LSTM-DNN)-based channel equalization approach to enhance signal recovery accuracy. …”
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Stratified allocation method for water injection based on machine learning: A case study of the Bohai A oil and gas field by Changlong Liu, Pingli Liu, Qiang Wang, Lu Zhang, Zechao Huang, Yuande Xu, Shaojiu Jiang, Le Zhang, Changxiao Cao

“…The relative error of the calculation results of the optimized neural network prediction model is approximately ±2.3 %. …”
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Attention Mechanism and Weighted Trend Loss for Wind Speed Correction by Liu Xu, Yang Hao, Liang Xiaoyun, Chen Jing, Li Qiaoping, Li Ruqing, Chen Min

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Lightweight deep learning system for automated bone age assessment in Chinese children: enhancing clinical efficiency and diagnostic accuracy by Pang Hai, Zhang Bin, Liu Kesheng, Li Cong, Xu Fei

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Utilizing active learning and attention-CNN to classify vegetation based on UAV multispectral data by Sheng Miao, Chuanlong Wang, Guangze Kong, Xiuhe Yuan, Xiang Shen, Chao Liu

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Development of a multi-level feature fusion model for basketball player trajectory tracking by Tao Wang

“…Firstly, a new model of athlete trajectory tracking is proposed, which improves the accuracy and efficiency of multi-target tracking by optimizing object detection algorithm and introducing hybrid branch network. …”
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Fault Diagnosis Method for Circuit Breaker Opening and Closing Coil Based on IEMD and GA-WNN by Tianhui LI, Xianhai PANG, Hui FAN, Li ZHEN, Chaomin GU, Chi DONG

“…On this basis, a circuit breaker fault diagnosis method is proposed by combining the improved genetic algorithm(GA) and wavelet neural network(WNN). This method uses the improved genetic algorithm to optimize the parameters of the neural network in order to solve the problem of parameter sensitivity of the wavelet neural network, thus improving the convergence speed of the diagnosis algorithm and the accuracy of fault diagnosis. …”
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