CNN-based vane-type vortex generator modelling by Koldo Portal-Porras, Unai Fernandez-Gamiz, Ekaitz Zulueta, Roberto Garcia-Fernandez, Xabier Uralde-Guinea

“…In order to obtain data for training the network, 20 different CFD simulations were conducted, considering the same inflow conditions but different vane heights and angles of attack of the VGs. …”
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An automatic ICD coding method for clinical records based on deep neural network by Yichao DU, Tong XU, Jianhui MA, Enhong CHEN, Yi ZHENG, Tongzhu LIU, Guixian TONG

“…With the increase in the number of the international classification of diseases (ICD) codes,the difficulty and cost of manual coding based on clinical records have greatly increased,and automatic ICD coding technology has attracted widespread attention.A multi-scale residual graph convolution network automatic ICD coding technology was proposed.This technology uses a multi-scale residual network to capture text patterns of different lengths of clinical text and extracts the hierarchical relationship between labels based on the graph convolutional neural network to enhance the ability of automatic coding.The experimental results on the real medical data set MIMIC-III show that the P@k and Micro-F1 of this method are 72.2% and 53.9%,respectively,which significantly improves the prediction performance.…”
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Multimodal Chinese Sarcasm Detection Integrating Audio Attributes and Textual Features by Huixin Wu, Yang Zang, Limeng Zhao, Hongyang Zhou

“…To extract relevant features at different levels, we use a multi-scale convolutional architecture. …”
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Wavelet-CNN for temporal data: Enhancing long-term stock price prediction via multi-resolution wavelet decomposition and CNN-based feature extraction by Komei Hiruta, Junsuke Senoguchi

“…Specifically, we first acquire components with different temporal resolutions using wavelet transform, then convert the wavelet-transformed data into images, and finally perform CNN processing to automatically extract useful temporal features for prediction. …”
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From Pixels to Diagnosis: Implementing and Evaluating a CNN Model for Tomato Leaf Disease Detection by Zamir Osmenaj, Evgenia-Maria Tseliki, Sofia H. Kapellaki, George Tselikis, Nikolaos D. Tselikas

“…Our work involved the implementation of a custom convolutional neural network (CNN) trained on a diverse dataset of tomato leaf images. …”
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Potato Leaf Disease Detection Based on a Lightweight Deep Learning Model by Chao-Yun Chang, Chih-Chin Lai

“…In this paper, we present a novel approach that integrates a lightweight convolutional neural network architecture, RegNetY-400MF, with transfer learning techniques to accurately identify seven different types of potato leaf diseases. …”
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A Novel Multi-Task Learning-Based Approach to Multi-Energy System Load Forecasting by Zain Ahmed, Mohsin Jamil, Ashraf Ali Khan

“…Multi-Energy Systems (MES) allow optimal interactions between different energy sources. Accurate load forecasting for such intricate systems would greatly enhance the performance and economic incentive to employ them. …”
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Protection Algorithm Based on Two-Dimensional Spatial Current Trajectory Image and Deep Learning for Transmission Lines Connecting Photovoltaic Stations by Panrun Jin, Jianling Liao, Wenqin Song, Xushan Zhao, Yankui Zhang

“…In this algorithm, the PV side current and the system side current are, respectively, mapped to the two-dimensional space plane as X- and Y-axes to form the current trajectory image. Under different fault conditions, they have obvious differences. …”
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Multiscale deformed attention networks for white blood cell detection by Xin Zheng, Qiqi Xu, Shiyi Zheng, Luxian Zhao, Deyang Liu, Liangliang Zhang

“…The Attention Multi-scale Sensing Module (AMSM) is designed to localize WBCs more accurately by fusing features at different scales and enhancing feature representation through a self-attention mechanism. …”
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Vision-Based UAV Localization on Various Viewpoints by Yee-Ming Ooi, Che-Cheng Chang, Yu-Min Su, Chiao-Ming Chang

“…Our findings illustrate the importance and relationship of various training data among the different performances of the model. The model achieves only 17% accuracy without applying rotational augmentation in the most practical scenario. …”
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Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases by HE Mengwen, MAI Sien, MA Han

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Knowledge graph-based entity alignment with unified representation for auditing by Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing Liu

“…Entity alignment involves linking entity pairs with the same real-world identity and aims to integrate heterogeneous knowledge across different knowledge graphs. However, most existing works do not effectively combine both attribute and relation representations into a unified framework for entity alignment, which is essential to link entities within an audit knowledge graph accurately. …”
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Research on Pantograph Defect Classification Based on Vibration Signals by Vytautas Gargasas, Kęstas Rimkus, Mindaugas Alekna, Andrius Knyš, Mindaugas Žilys, Algimantas Valinevičius

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Does Using Artificial Intelligence in Citizen Science Support Volunteers’ Learning? An Experimental Study in Ornithology by Khrystyna Pankiv, Laure Kloetzer

“…Further research with different participant profiles and project designs is needed to understand how to optimise volunteer productivity, retention, and learning in AI-assisted CS projects.…”
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Hypergraph User Embeddings and Session Contrastive Learning for POI Recommendation by Yan Zhang, Bin Wang, Qian Zhang, Sulei Zhu, Yan Ma

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Improved Segmentation of Infant Retinal Images and Quantitative Vascular Analysis by Ying Wang, Xiaoyu Zheng, Chunlei He, Jianfeng Zhang, Shoujun Huang

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Comparative Analysis of Deep Learning Architectures for Macular Hole Segmentation in OCT Images: A Performance Evaluation of U-Net Variants by H. M. S. S. Herath, S. L. P. Yasakethu, Nuwan Madusanka, Myunggi Yi, Byeong-Il Lee

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Classification and Physical Characteristic Analysis of Fermi-GBM Gamma-Ray Bursts Based on Deep Learning by Jia-Ming Chen, Ke-Rui Zhu, Zhao-Yang Peng, Li Zhang

“…Early long- and short-burst classification based on duration is not convincing owing to the significant overlap in duration plot, which leads to different views on the classification results. We propose a new classification method based on convolutional neural networks and adopt a sample including 3774 GRBs observed by Fermi-GBM to address the T _90 overlap problem. …”
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Robust Multi-Input Multi-Output Analysis for Crop Row Segmentation and Furrow Line Detection in Diverse Agricultural Fields by Muhammad Ibrahim Zain Ul Abideen, Dewa Made Sri Arsa, Talha Ilyas, Hyunggi Jo, Sang Cheol Kim, Hyongsuk Kim

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ARAN: Age-Restricted Anonymized Dataset of Children Images and Body Measurements by Hezha H. MohammedKhan, Cascha Van Wanrooij, Eric O. Postma, Çiçek Güven, Marleen Balvert, Heersh Raof Saeed, Chenar Omer Ali Al Jaf

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