Vision-Based UAV Localization on Various Viewpoints by Yee-Ming Ooi, Che-Cheng Chang, Yu-Min Su, Chiao-Ming Chang

“…In the literature, an existing vision-based study is proposed to position the drone by a shallow Convolutional Neural Network (CNN). However, they only consider a constant viewpoint (towards the north). …”
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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

“…Our proposed KG-Marfia first extracts entity representations by addressing the imbalance of attributes and relations, and then designs a stacked graph convolutional network as an encoder to fuse attribute and relation information, learning unified representations for entities. …”
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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

“…The Cornell Lab has also developed a mobile application, Merlin, which uses a deep convolutional neural network to help users automatically identify bird species from photos, sounds (converted to spectrograms), or descriptions. …”
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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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DART-Vetter: A Deep Learning Tool for Automatic Triage of Exoplanet Candidates by Stefano Fiscale, Laura Inno, Alessandra Rotundi, Angelo Ciaramella, Alessio Ferone, Christian Magliano, Luca Cacciapuoti, Veselin Kostov, Elisa V. Quintana, Giovanni Covone, Maria Teresa Muscari Tomajoli, Vito Saggese, Luca Tonietti, Antonio Vanzanella, Vincenzo Della Corte

“…To further improve the robustness of these models, it is necessary to exploit the complementarity of data collected from different transit surveys such as NASA’s Kepler, Transiting Exoplanet Survey Satellite (TESS), and, in the near future, the ESA Planetary Transits and Oscillation of stars mission. …”
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An Inverted Residual Cross Head Knowledge Distillation Network for Remote Sensing Scene Image Classification by Cuiping Shi, Mengxiang Ding, Liguo Wang

“…Convolutional neural networks are extensively used in RSSC tasks, where convolution focuses more on the high-frequency components of the image. …”
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Cell-Type Annotation for scATAC-Seq Data by Integrating Chromatin Accessibility and Genome Sequence by Guo Wei, Long Wang, Yan Liu, Xiaohui Zhang

“…Cross-omics approaches, which rely on single-cell RNA sequencing (scRNA-seq) as a reference, often struggle with data alignment due to fundamental differences between transcriptional and chromatin accessibility modalities. …”
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DB-Net: A Dual-Branch Hybrid Network for Stroke Lesion Segmentation on Non-Contrast CT Images by Xiao Jia, He Dong, Jiashu Xu, Yanhong Zhang, Yihua Lan

“…To address these challenges, this study proposes a two-branch hybrid network combining a convolutional neural network (CNN) with a Transformer framework. …”
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End-to-End Multi-Scale Adaptive Remote Sensing Image Dehazing Network by Xinhua Wang, Botao Yuan, Haoran Dong, Qiankun Hao, Zhuang Li

“…The design of this module can extract important image features at different scales. By expanding convolution, the receptive field is expanded to capture broader contextual information, thereby obtaining a more global feature representation. …”
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Predicting Gender from Twitter Text Messages Using Methods Based on Artificial Intelligence and Text Analysis by Md. Nyem Hasan Bhuiyan, Anisur Rahman

“…For this purpose, 2 different approaches, namely Neural Networks (NNs) and Machine Learning (ML), were used for classification. …”
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Research on CNC Machine Tool Spindle Fault Diagnosis Method Based on DRSN–GCE Model by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Jiaming Chen, Xuelian Yu

“…In the first step, the data are preprocessed by adding different noises with different ratios of signal to noise and different frequencies to the vibration signals. …”
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A Lightweight Forward–Backward Independent Temporal-Aware Causal Network for Speech Emotion Recognition by Sijia Fei, Qiang Feng, Fei Gao

“…Finally, different levels of forward-backward features are fused to refine historical-future emotion change trends and better perceive the details of emotion changes. …”
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An incremental learning framework for pipeline weld crack damage identification and leakage rate prediction by Jing Huang, Zhifen Zhang, Yanlong Yu, Yongjie Li, Shuai Zhang, Rui Qin, Ji Xing, Wei Cheng, Guangrui Wen, Xuefeng Chen

“…Then, according to the attenuation characteristics of acoustic emission signals, a portable input-attention module is designed to add different weights to the input sequence. Finally, the accurate prediction of leakage rate under different conditions is realized based on the temporal convolutional network. …”
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