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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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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Augmented self attention network for liver tumour segmentation of CT images by Bilga Jacob, R.S Vinod Kumar, S.S. Kumar

“…The architecture achieved a higher level of Dice score (DSC) – 0.923, Intersection-Over-Union (IoU) – 0.913, Volumetric Overlap Error (VOE) – 0.086 and Relative Volume Difference (RVD) – 3.85 for liver tumour segmentation which is remarkable.…”
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A Deep Neural Network Framework for Dynamic Two-Handed Indian Sign Language Recognition in Hearing and Speech-Impaired Communities by Vaidhya Govindharajalu Kaliyaperumal, Paavai Anand Gopalan

“…One may consider such as a connecting bridge for bridging communication gaps for the hearing- and speech-impaired, even though it remains as an advanced method for hand gesture expression along with identification through the various different unidentified signals to configure their palms. …”
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