Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization by Amandeep Kaur, Shalli Rani, Mohammad Shabaz

“…The BAM selectively amplifies spatial and channel-specific features, thereby augmenting the network’s capacity to preserve natural hues and intricate details. …”
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Capacity Prognostics of Marine Lithium-Ion Batteries Based on ICPO-Bi-LSTM Under Dynamic Operating Conditions by Qijia Song, Xiangguo Yang, Telu Tang, Yifan Liu, Yuelin Chen, Lin Liu

“…Finally, to prevent the interference of test data during model training, which could lead to evaluation errors, the training dataset is used for parameter fitting, the validation dataset for hyperparameter adjustment, and the test dataset for the model performance evaluation. …”
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Development and validation of AI-based automatic segmentation and measurement of thymus on chest CT scans by Yusheng Guo, Bingxin Gong, Guowei Jiang, Wang Du, Shuangfeng Dai, Qi Wan, Dongyong Zhu, Chanyuan Liu, Yi Li, Qing Sun, Qianqian Fan, Bo Liang, Lian Yang, Chuansheng Zheng

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Spatial Orientation Relation Recognition for Water Surface Targets by Peiyong Gong, Kai Zheng, Yi Jiang, Huixuan Zhao, Xiao Liang, Zhiwen Feng, Wenbin Huang

“…The WST-SOVF algorithm encodes the spatial orientation relation into the learning framework of a new deep convolutional neural network model, which comprises two distinct branches: the T-branch and the S-branch, both designed for the spatial feature extraction. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

“…These features are then processed through an LSTM network and converted into a format suitable for the reconstructive GAN. …”
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Prediction of the Next Solar Rotation Synoptic Maps Using an Artificial Intelligence–based Surface Flux Transport Model by Hyun-Jin Jeong, Mingyu Jeon, Daeil Kim, Youngjae Kim, Ji-Hye Baek, Yong-Jae Moon, Seonghwan Choi

“…Synoptic maps, which represent global magnetic field distributions on the solar surface, have been widely used as initial boundary conditions in the Sun and space-weather prediction models. Here we train and evaluate our deep-learning model, based on the Pix2PixCC architecture, using data sets of Solar Dynamics Observatory/Helioseismic and Magnetic Imager, Solar and Heliospheric Observatory/Michelson Doppler Imager, and National Solar Observatory/Global Oscillation Network Group synoptic maps with a resolution of 360 by 180 (longitude and sine latitude) from 1996 to 2023. …”
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Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces by M.A. Dalhat, Sami A. Osman

“…Three CNN architectures (Simple model, SqueezeNet, and Xception) were evaluated to compare their performance and feature extraction capabilities. …”
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Filling the data gap between GRACE and GRACE-FO based on a two-step reconstruction method by Fengmin Hu, Beibei Yang, Zushuai Wei, Changlu Cui, Lingkui Meng

“…The model was evaluated on a global scale across 40 basins and at a grid scale. …”
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SYSTEMIC GENERATION OF SOLVING NECESSARY PROFESSIONAL THE TASKS by Vladimir M. Nesterenko

“…It is argued, that if the information is represented in the form of parametric networks based on the principles of the brain, then the student will be much faster to process and evaluate such information. …”
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Flat U-Net: An Efficient Ultralightweight Model for Solar Filament Segmentation in Full-disk Hα Images by GaoFei Zhu, GangHua Lin, Xiao Yang, Cheng Zeng

“…Solar filaments are one of the most prominent features observed on the Sun, and their evolutions are closely related to various solar activities, such as flares and coronal mass ejections. …”
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Development and validation of deep learning- and ensemble learning-based biological ages in the NHANES study by Yushu Huang, Xifan Yang, Qi Wang, Adila Abula, Yue Dong, Wenyuan Li, Wenyuan Li

“…These features were utilized to train deep neural networks (DNN) and ensemble learning models, specifically the Deep Biological Age (DBA) and Ensemble Biological Age (EnBA), with chronological age (CA) as the reference label. …”
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Relationship of transforming growth factor β1 with diabetic retinopathy in type 2 diabetes by A.S. Hudz, V.A. Serhiyenko, I.V. Kudryl, V.G. Guryanov, M.I. Kovtun, S.V. Ziablitsev

“…TGF-β1 in blood serum and IOF was evaluated by enzyme-linked immunosorbent assay (Invitrogen Thermo Fisher Scientific, USA). …”
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Media Communications of Executive Power: Assessing Effectiveness by E. A. Bazhenova, M. A. Shirinkina

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Tabular Data Models for Predicting Art Auction Results by Patryk Mauer, Szczepan Paszkiel

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Transforming tabular data into images via enhanced spatial relationships for CNN processing by Hameedah A. Alenizy, Jawad Berri

“…Abstract Convolutional neural networks (CNNs), renowned for their efficiency in image analysis, have revolutionized pattern and structure recognition in visual data. …”
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Civil Aircraft Landing Attitude Ultra-Limit Warning System Based on mRMR-LSTM by Fei Lu, Tong Jing, Chunsheng Xie, Haonan Chen

“…Subsequently, through data pretreatment methods such as data cleaning, frequency normalization, data standardization, and feature classification, the experimental dataset is transformed into a form recognizable by machine learning algorithms and neural network models. …”
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Toward Personal Identification Using Multi-Angle-Captured Ear Images: A Feasibility Study by Ryuhi Fukuda, Yuto Yokoyanagi, Chotirose Prathom, Yoshifumi Okada

“…Further, we performed Gradient-weighted Class Activation Mapping to visualize the feature points that contribute to the identification process, identifying the helix region of the ear as a key feature point. …”
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An optimized deep learning based hybrid model for prediction of daily average global solar irradiance using CNN SLSTM architecture by Yuvaraj Mariappan, Karthikeyan Ramasamy, Durgadevi Velusamy

“…First, we have selected 14 significant relevant features from the dataset using recursive feature elimination techniques. …”
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U-MGA: A Multi-Module Unet Optimized with Multi-Scale Global Attention Mechanisms for Fine-Grained Segmentation of Cultivated Areas by Yun Chen, Yiheng Xie, Weiyuan Yao, Yu Zhang, Xinhong Wang, Yanli Yang, Lingli Tang

“…In the reconstruction phase, the introduction of the Multi-Scale Contextual Module (MCM) and Group Aggregation Bridge (GAB) significantly enhances the efficiency and accuracy of multi-scale and fine-grained feature utilization. The experiments conducted on an arable land dataset based on GF-2 imagery and a publicly available dataset show that U-MGA outperforms mainstream networks (Unet, A2FPN, Segformer, FTUnetformer, DCSwin, and TransUnet) across six evaluation metrics (Overall Accuracy (OA), Precision, Recall, F1-score, Intersection-over-Union (IoU), and Kappa coefficient). …”
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Key Frame Detection in Badminton Swings and Its Application to Physical Education by Jen-Hao Hsu, Chi-Chuan Lee, Jing-Yuan Chang, Duan-Shin Lee

“…Comparative studies show that models with graph convolutional networks, a prominent approach commonly used in skeleton-based human action recognition, outperform other existing methods in terms of accuracy and reliability. …”
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