Hybrid feature-time series neural network for predicting ACL forces in martial artists with resistive braces after reconstruction by Dongyue Li, Haojie Li, Yang Hang

“…A feature-embedded temporal convolutional neural network (TCN) fused time-series gait data (T3) with static features (T0-T3) to predict ACL forces.ResultsThe hybrid TCN model achieved superior ACL force prediction accuracy, with a mean R2 = 0.63 (EG), R2 = 0.58 (CG), and R2 = 0.62 (combined cohort) in three-fold cross-validation. …”
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Enhanced Osteoporosis Detection Using Artificial Intelligence: A Deep Learning Approach to Panoramic Radiographs with an Emphasis on the Mental Foramen by Robert Gaudin, Wolfram Otto, Iman Ghanad, Stephan Kewenig, Carsten Rendenbach, Vasilios Alevizakos, Pascal Grün, Florian Kofler, Max Heiland, Constantin von See

“…Dual-energy X-ray absorptiometry (DXA) scans, the current gold standard, are typically used post-fracture, highlighting the need for early detection tools. …”
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3D-CNN detection of systemic symptoms induced by different Potexvirus infections in four Nicotiana benthamiana genotypes using leaf hyperspectral imaging by Rizos-Theodoros Chadoulis, Ioannis Livieratos, Ioannis Manakos, Theodore Spanos, Zeinab Marouni, Christos Kalogeropoulos, Constantine Kotropoulos

“…In this study, the use of 3D Convolutional Neural Networks (3D-CNNs) was explored to detect presymptomatic viral infections in the model plant Nicotiana benthamiana L. and assess the generalization of these models across different plant genotypes. …”
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Application of a Transfer Learning Model Combining CNN and Self-Attention Mechanism in Wireless Signal Recognition by Wu Wei, Chenqi Zhu, Lifan Hu, Pengfei Liu

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Efficient super resolution-based detail injection network for multispectral pan-sharpening by Yaxu Wang, Xiaobo Luo, Hongwei Ye

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FFLKCDNet: First Fusion Large-Kernel Change Detection Network for High-Resolution Remote Sensing Images by Bochao Chen, Yapeng Wang, Xu Yang, Xiaochen Yuan, Sio Kei Im

“…FFLKCDNet features a Bi-temporal Feature Fusion Module (BFFM) to fuse remote sensing features from different temporal scales, and an improved ResNet network (RAResNet) that combines large-kernel convolution and multi-attention mechanisms to enhance feature extraction. …”
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Tumor segmentation in whole-slide histology images using deep learning by V. A. Kovalev, V. A. Liauchuk, A. A. Kalinovski, M. V. Fridman

“…The procedure capitalizes on convolutional neural networks and Deep Learning methods. …”
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Deep Learning-Based Algorithms for Real-Time Lung Ultrasound Assisted Diagnosis by Mario Muñoz, Adrián Rubio, Guillermo Cosarinsky, Jorge F. Cruza, Jorge Camacho

“…We introduce a specialized deep learning model designed and trained to facilitate the analysis and interpretation of lung ultrasound images by automating the detection and location of pulmonary features, including the pleura, A-lines, B-lines, and consolidations. Employing Convolutional Neural Networks (CNNs) trained on a semi-automatically annotated dataset, the model delineates these pulmonary patterns with the objective of enhancing diagnostic precision. …”
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Research on Seismic Signal Denoising Model Based on DnCNN Network by Li Duan, Jianxian Cai, Li Wang, Yan Shi

“…These limitations hinder effective noise removal, resulting in suboptimal signal-to-noise ratios (SNRs) and post-denoising waveform distortion. To address these shortcomings, this study introduces a novel denoising approach leveraging a DnCNN network. …”
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The Recognition of Protein Methylation Sites Based on CNN and Bi-LSTM Models by MA Chizhuo, ZHOU Wenjing, LEI Zhichao, WANG Chuzheng

“…Methylation is a protein Post-Translational Modification (PTM) that regulates cell function ,which can provide guidance and help for research in the fields of gene regulation and disease prediction. …”
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Predicting user's movement path in indoor environments using the stacked deep learning method and the fuzzy soft‐max classifier by Masoumeh Bourjandi, Meisam Yadollahzadeh‐Tabari, Mehdi GolsorkhtabariAmiri

“…In this work, a three‐phase stacked method named CNN‐LSTM‐FSC is proposed, which uses the Convolutional Neural Network (CNN), Long Short‐Term Memory (LSTM), and Fuzzy Soft‐max Classifier (FSC) to overcome the mentioned constraints. …”
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Lightweight CNN-based seizure classification via leveraging chimera states in iEEG recordings by Fatemeh Azad, Saeed Bagheri Shouraki, Soheila Nazari, Mansun Chan

“…These images are processed by a streamlined convolutional neural network (CNN) framework, which classifies iEEG recordings into pre-ictal, ictal, and post-ictal events with robust patient-independent performance. …”
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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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