Early detection of Citrus Huanglongbing by UAV remote sensing based on MGA-UNet by Naibo Ye, Wenyong Mai, Feng Qin, Sen Yuan, Bo Liu, Zaiyuan Li, Conghui Liu, Fanghao Wan, Wanqiang Qian, Zhongzhen Wu, Xi Qiao

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Hearing loss is associated with decreased default-mode network connectivity in individuals with mild cognitive impairment by Nicole Grant, Natalie Phillips

“…We used independent component analyses on resting-state functional magnetic resonance imaging data to identify the default-mode network (DMN). …”
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Unbalancing Datasets to Enhance CNN Models Learnability: A Class-Wise Metrics-Based Closed-Loop Strategy Proposal by Somayeh Shahrabadi, Victor Alves, Emanuel Peres, Raul Morais Dos Santos, Telmo Adao

“…To compare regular (linear) and MbCL-based approaches, a couple of contextually distinct datasets were considered to broaden consistency analysis across some diversity. Using these datasets, 72 models with varying configurations – including different convolutional neural network architectures, initial learning rates, and optimizers – were initially trained and then evaluated against imagery test sets. …”
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MRTMD: A Multi-Resolution Dataset for Evaluating Object Detection in Traffic Monitoring Systems by Mark Bugeja, Matthias Bartolo, Matthew Montebello, Dylan Seychell

“…However, their effectiveness depends heavily on the quality of the input data, especially image resolution. With high-resolution cameras, especially 4K, balancing image quality, detection accuracy, and system efficiency is critical. …”
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Two-stage augmentation for detecting malignancy of BI-RADS 3 lesions in early breast cancer by Huanhuan Tian, Li Cai, Yu Gui, Zhigang Cai, Xianfeng Han, Jianwei Liao, Li Chen, Yi Wang

“…We conducted a comparative analysis between our model and four radiologists in breast imaging diagnosis. …”
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Deep learning-based dual optimization framework for accurate thyroid disease diagnosis using CNN architectures by Zeeshan Ali Haider, Nasser A Alsadhan, Fida Muhammad Khan, Waleed Al-Azzawi, Inam Ullah Khan, Inam Ullah

“…Further research will also explore real-time ultrasound analysis and multi-modal data integration, such as combining medical images with patient history, to enhance diagnostic accuracy. …”
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Comparative convolutional neural networks for perovskite solar cell PCE predictions by Milan Harth, D. Kishore Kumar, Said Kassou, Kenza El Idrissi, Ritesh Kant Gupta, Yonatan Daniel, Ofry Makdasi, Iris Visoly-Fisher, Alessio Gagliardi

“…This comparative technique significantly outperforms traditional methods that attempt to directly infer PCE from a single image. Furthermore, it demonstrates high effectiveness in low-data regimes, using only 115 samples. …”
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A simple clustering approach to map the human brain's cortical semantic network organization during task by Yunhao Zhang, Shaonan Wang, Nan Lin, Lingzhong Fan, Chengqing Zong

“…Specifically, we analyzed functional magnetic resonance imaging (fMRI) data from 11 subjects, each exposed to 672 concepts, and correlated this with semantic rating data related to these concepts. …”
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Neural connectivity and balance control in aging: Insights from directed cortical networks during sensory conflict by Guozheng Wang, Yi Yang, Xiaoxia Liu, Anke Hua, Xin Luo, Yiming Cai, Yanhua Song, Jian Wang, Jun Liu

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Hyperspectral segmentation of plants in fabricated ecosystems by Petrus H. Zwart, Petrus H. Zwart, Petrus H. Zwart, Peter Andeer, Trent R. Northen

“…Downstream analysis focuses on using the segmented data for processing spectral data, enabling monitoring of plant health. …”
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Unravelling lipid heterogeneity: Advances in single-cell lipidomics in cellular metabolism and disease by Sutanu Sarkar, Rajgourab Ghosh

“…Recent advancements in single-cell analysis have revolutionized our understanding of cellular heterogeneity, particularly in lipid metabolism. …”
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Cross-Feature Hybrid Associative Priori Network for Pulsar Candidate Screening by Wei Luo, Xiaoyao Xie, Jiatao Jiang, Linyong Zhou, Zhijun Hu

“…Through comparative analysis of feature weight similarity between subimages and average fusion weights, CFHAPNet efficiently identifies and filters genuine pulsar signals from candidate images collected across astronomical observatories. …”
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Forecast Model of TV Show Rating Based on Convolutional Neural Network by Lingfeng Wang

“…Therefore, this paper introduces the convolutional neural network structure to predict the TV program rating data. …”
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A Multimodal Semantic-Enhanced Attention Network for Fake News Detection by Weijie Chen, Yuzhuo Dang, Xin Zhang

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Enhancing colorectal polyp classification using gaze-based attention networks by Zhenghao Guo, Yanyan Hu, Peixuan Ge, In Neng Chan, Tao Yan, Pak Kin Wong, Shaoyong Xu, Zheng Li, Shan Gao

“…The class activation maps generated by the proposed network also indicate that the endoscopist’s gaze-attention information, as auxiliary prior knowledge, increases the accuracy of colorectal polyp classification, offering a new solution to the field of medical image analysis.…”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

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Multimodal Magnetic Resonance Findings in Parkinson’s Disease With “Antecedent Essential Tremor”: A Case Series of a Large Kindred by Kong Y, Yao L, Xiao X, Chen A, Wang K, Yan H, Sun R, Liu R, Kong Q

“…The clinical characteristics, genetic testing and multimodal MRI data of 16 family members were collected. Multimodal MRI analysis included structural MRI, diffusion tensor imaging (DTI) and tractography, and quantitative susceptibility mapping (QSM).Results: Two second-generation family members diagnosed PD had ET history before PD performance appeared, five third-generation family members were diagnosed with ET. …”
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Automatic detection and visualization of temporomandibular joint effusion with deep neural network by Yeon-Hee Lee, Seonggwang Jeon, Jong-Hyun Won, Q.-Schick Auh, Yung-Kyun Noh

“…The prediction accuracy of the ensemble model was higher than that of the human experts when all the data were used (74.21% vs. 67.71%, p < 0.05). A deep neural network (DNN) was developed to process multimodal data, including MRI and patient clinical data. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Therefore, developing a more effective method to address pedestrian occlusion detection is essential for enhancing the performance of pedestrian detectors.MethodsProposed the Global Feature Focusing and Information Enhancement Network (GFFIE-Net). The method starts with feature extraction employ HRNet-W32 as the backbone network to generate multi-scale feature maps with different resolutions (1/4, 1/8, 1/16, and 1/32 of the input image). …”
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Providing a development model for the effectiveness of persuasive advertising in social networks by Hamzeh Hessani Khabr, Payam Paslari, Mehdi Bagheri, Saeed Muradpour

“…A semi-structured interview was used to collect information. Data-based and coding method was used for data analysis. …”
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