Underwater Visual Object Tracking Method Based on Scene Perception by Qianwei HU, Daiwei WANG, Renjie LI, Xiaofan YU, Bin KANG, Ruoyu SU

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Novel Deep Learning Method in Hip Osteoarthritis Investigation Before and After Total Hip Arthroplasty by Roel Pantonial, Milan Simic

“…Based on the human gait cycle’s features, a hybrid Long Short-Term Memory–Convolutional Neural Network (HLSTM-CNN) is designed for the classification of healthy/HOA/THA gaits. …”
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Three-Dimensional Automated Breast Ultrasound (ABUS) Tumor Classification Using a 2D-Input Network: Soft Voting or Hard Voting? by Shaode Yu, Xiaoyu Liang, Songnan Zhao, Yaoqin Xie, Qiurui Sun

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Automated depression detection via cloud based EEG analysis with transfer learning and synchrosqueezed wavelet transform by Sara Bagherzadeh, Mohammad Reza Norouzi, Amirhesam Ghasri, Pouya Tolou Kouroshi, Sepideh Bahri Hampa, Fatemeh Farokhshad, Ahmad Shalbaf

“…Abstract Post-COVID-19, depression rates have risen sharply, increasing the need for early diagnosis using electroencephalogram (EEG) and deep learning. …”
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Dynamic deep learning based super-resolution for the shallow water equations by Maximilian Witte, Fabrício R Lapolli, Philip Freese, Sebastian Götschel, Daniel Ruprecht, Peter Korn, Christopher Kadow

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Trading Community Analysis of Countries’ Roll-On/Roll-Off Shipping Networks Using Fine-Grained Vessel Trajectory Data by Shichen Huang, Tengda Sun, Jing Shi, Piqiang Gong, Xue Yang, Jun Zheng, Huanshuai Zhuang, Qi Ouyang

“…This method assesses the complexity, sparsity, homogeneity, modularity, and hierarchy of the RO/RO shipping network across various ports and countries and employs the graph convolutional neural network (GCN) model to extract network features for community detection. …”
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A CNN-LSTM Phase Compensation Method for Unidirectional Two-way Radio Frequency Transmission System by Jiahui Cheng, Zhengkang Wang, Yaojun Qiao, Hao Gao, Chenxia Liu, Zhuoze Zhao, Jie Zhang, Baodong Zhao, Bin Luo, Song Yu

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Hyperspectral Image Classification Based on Fractional Fourier Transform by Jing Liu, Lina Lian, Yuanyuan Li, Yi Liu

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Enhancing TextGCN for depression detection on social media with emotion representation by Huimin Mao, Qing Han

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Enhancing plant disease detection through deep learning: a Depthwise CNN with squeeze and excitation integration and residual skip connections by Asadulla Y. Ashurov, Mehdhar S. A. M. Al-Gaashani, Nagwan A. Samee, Reem Alkanhel, Ghada Atteia, Hanaa A. Abdallah, Mohammed Saleh Ali Muthanna

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Apple Watercore Grade Classification Method Based on ConvNeXt and Visible/Near-Infrared Spectroscopy by Chunlin Zhao, Zhipeng Yin, Yushuo Tan, Wenbin Zhang, Panpan Guo, Yaxing Ma, Haijian Wu, Ding Hu, Quan Lu

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Hyperspectral Image Classification Based on Two-Branch Feature Fusion Network by Qiongdan Huang, Liang Li, Mengyang Zhao, Jiapeng Wang, Shilin Kang

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Emotion Recognition Model of EEG Signals Based on Double Attention Mechanism by Yahong Ma, Zhentao Huang, Yuyao Yang, Shanwen Zhang, Qi Dong, Rongrong Wang, Liangliang Hu

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Comparison of Surgical Outcomes between Endovenous Laser Ablation and Conventional Surgery in Patients with Lower Limb Varicose Veins: A Prospective Interventional Study by Mannam Viswateja, Deepak R Chavan, Vijaya Patil, Vikram U Sindagikar

“…Introduction: Dilated, convoluted, subcutaneous veins measuring more than 3 mm in diameter when measured while upright and exhibiting reflux are called varicose veins. …”
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Advanced Brain Tumor Segmentation With a Multiscale CNN and Conditional Random Fields by Ala Guennich, Mohamed Othmani, Hela Ltifi

“…These modifications allow us to reduce the number of layers in our network while significantly improving the accuracy of 3D medical image segmentation. For post-processing the network’s soft segmentation, we employ a 3D fully connected Conditional Random Field, which effectively removes false positives. …”
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Multi-modal expert system for automated durian ripeness classification using deep learning by Santi Sukkasem, Watchareewan Jitsakul, Phayung Meesad

“…Accurate classification of durian ripeness is essential for quality control and minimizing post-harvest losses. Manual inspection remains subjective and inconsistent, prompting the need for automated methods. …”
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R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals by Kamirul Kamirul, Odysseas A. Pappas, Alin M. Achim

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Tillage and biomass detection for estimating winter-time cropland management practices with satellite remote sensing by Maria Yli-Heikkilä, Arto Klami, Samantha Wittke, Markku Luotamo, Pinja Mero, Petri Pellikka, Janne Heiskanen, Mwaba Hiltunen, Kari Luojus, Golda Prakasam, Mikko Strahlendorff, Markus Törmä, Mi Sulkava

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Hyperspectral imaging-driven deep learning approach: Asymptomatic stage detection and severity grading of tomato yellow leaf curl disease by Junzhi Chen, Wenshan Zhong, Xuejun Yue, Ziyu Ding, Mengdan Du, Xuantian Li, Biao Chen, Haifeng Li, ZiFu He, Xiaoman She, Yafei Tang

“…Comparative experiments with three baseline models (2D CNN, 3D CNN, and HybridSN) demonstrated that SSDBRN achieved an early-infection detection accuracy of 84.2 % (5–7 days post-inoculation) and 96.2 % severity classification accuracy across six stages, significantly outperforming the baseline models. …”
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Computational methods and technical means of processing signals of side electromagnetic emanation by Danil A. Shinyaev, Leonid N. Kessarinskiy, Egor A. Simakhin

“…The aim of this work is to develop a method to improve the quality of the reconstructed image based on the signals of side electromagnetic fields using post-image processing. To do this, the paper considers the problem of analyzing the side electromagnetic radiation from video displays and ways to solve it. …”
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