Hyperspectral Detection of Metal Element Concentration in Vegetation Canopies: A Case Study of Fe and Mo by Daming Wang, Veronika Kopačková-Strnadová, Bo Zhang, Jing Zhang, Feicui Wang, Junquan Yang

“…Regarding the wheat spectral analysis, the absorption features at specified wavelengths were identified as significant for creating valid linear models to analyze the effect of Fe and Mo in wheat leaf and spike spectra. …”
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Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology by Andrew Broad, Alexander Wright, Clare McGenity, Darren Treanor, Marc de Kamps

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Enhancing Fall Detection Accuracy: The Ground-Face Coordinate System for 3D Accelerometer Data by Abdullah Talha Sözer

“…To assess the potential of the vertical component of ground-face referenced accelerometer signals for FD, it was compared with the commonly used acceleration magnitude signal. Detailed analysis was conducted using frequently preferred features in FD studies, and fall detection was performed with various classifiers. …”
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Multimodal AI-driven object detection with uncertainty quantification for cardiovascular risk assessment in autistic patients by Ling Tang, Chengchao Shen

“…Conventional methods, relying heavily on manually extracted features and rule-based analysis, often fail to capture subtle cardiovascular abnormalities, leading to suboptimal clinical outcomes.MethodsTo address these limitations, we propose an AI-driven object detection framework that leverages advanced deep learning techniques for automated, accurate cardiovascular risk assessment in autistic patients. …”
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Flexible Polymer-Based Electrodes for Detecting Depression-Related Theta Oscillations in the Medial Prefrontal Cortex by Rui Sun, Shunuo Shang, Qunchen Yuan, Ping Wang, Liujing Zhuang

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Sweat-Sensing Patches with Integrated Hydrogel Interface for Resting Sweat Collection and Multi-Information Detection by Lei Lu, Qiang Sun, Zihao Lin, Wenjie Xu, Xiangnan Li, Tian Wang, Yiming Lu, Huaping Wu, Lin Cheng, Aiping Liu

“…Additionally, a colorimetric module utilizing glucose oxidase and peroxidase is also integrated into the platform for cost-effective and efficient glucose detection through a color change that can be quantified via RGB analysis. …”
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Enhanced Vision-Based Quality Inspection: A Multiview Artificial Intelligence Framework for Defect Detection by Geethika Bhavanasi, Davy Neven, Manuel Arteaga, Sina Ditzel, Sam Dehaeck, Abdellatif Bey-Temsamani

“…We propose MV-UNet, a novel early fusion architecture that aligns and aggregates multiview features using a transformation block to enhance detection accuracy. …”
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Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism by Sakorn Mekruksavanich, Wikanda Phaphan, Anuchit Jitpattanakul

“…Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis require enhancement in the creation of dependable detection approaches. …”
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Integrated geophysical prospecting for deep ore detection in the Yongxin gold mining area, Heilongjiang, China by Yechang Yin, Jun Chen, Zhonghai Zhao, Yuanjiang Yang, Chenglu Li, Haina Li, Xiang Zhao

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A CNN-Transformer Fusion Model for Proactive Detection of Schizophrenia Relapse from EEG Signals by Sana Yasin, Muhammad Adeel, Umar Draz, Tariq Ali, Mohammad Hijji, Muhammad Ayaz, Ashraf M. Marei

“…In this study, we propose a CNN-Transformer fusion model that leverages the complementary strengths of Convolutional Neural Networks (CNNs) and Transformer-based architectures to process electroencephalogram (EEG) signals enriched with clinical and sentiment-derived features. This hybrid framework enables joint spatial-temporal modeling of relapse indicators, allowing for a more nuanced and patient-specific analysis. …”
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Vision-based approach to knee osteoarthritis and Parkinson’s disease detection utilizing human gait patterns by Zeeshan Ali, Jihoon Moon, Saira Gillani, Sitara Afzal, Muazzam Maqsood, Seungmin Rho

“…However, in this study, a novel approach is proposed in which spatiotemporal features are extracted via deep learning methods with a transfer learning paradigm. …”
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Dim and Small Target Detection Based on Improved Bilateral Filtering and Gaussian Motion Probability Estimation by Fan Xiangsuo, Qin Wenlin, Feng Gaoshan, Huang Qingnan, Min Lei

“…Finally, we construct the grayscale probability model to realize the multi-frame correlation detection, which combining the grayscale features and the motion characteristics of the target. …”
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Benchmarking 21 Open-Source Large Language Models for Phishing Link Detection with Prompt Engineering by Arbi Haza Nasution, Winda Monika, Aytug Onan, Yohei Murakami

“…Phishing URL detection is critical due to the severe cybersecurity threats posed by phishing attacks. …”
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Research on wind turbine blade fault detection based on DenseNet-TL combined with ELM by Dianming WANG, Xue PAN, Jian MA, Yuzhang DAI, Chengjun SUN, Shibin LI, Xiaoju YIN

“…The image samples are collected as training set, and the image features are effectively extracted using the improved DenseNet, which is combined with Extreme Learning Machines to improve the classification accuracy of the detection. 8000 images were collected, and the analysis results for the test set of images show that the detection accuracy of this model is higher than that of the DenseNet, ResNet and AlexNet models of migration learning, reaching more than 99%, and obtaining a more accurate preventive detection of wind turbine blade faults.…”
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Fast COVID-19 Detection from Chest X-Ray Images Using DCT Compression by Fatma Taher, Reem T. Haweel, Usama M. H. Al Bastaki, Eman Abdelwahed, Tariq Rehman, Tarek I. Haweel

“…Currently, real-time quantitative reverse transcription-PCR (rqRT-PCR) is popular for coronavirus detection due to its high specificity, simple quantitative analysis, and higher sensitivity than conventional RT-PCR. …”
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Enhancing EEG-Based Emotion Detection with Hybrid Models: Insights from DEAP Dataset Applications by Badr Mouazen, Ayoub Benali, Nouh Taha Chebchoub, El Hassan Abdelwahed, Giovanni De Marco

“…Furthermore, we employed SHapley Additive exPlanations (SHAP) to enhance model interpretability, offering deeper insights into the contribution of individual features to classification decisions. A comparative analysis with existing methods highlights the novelty and advantages of our approach, particularly in terms of accuracy, interpretability, and computational efficiency. …”
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Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection by Qingming Ye, Zhilu Wang, Yi Lou, Yang Yang, Jue Hou, Zheng Liu, Weiguang Liu, Jiayu Li

“…However, their diagnosis can be particularly challenging due to the anatomical characteristics and imaging features of the pediatric skeleton. In recent years, convolutional neural networks (CNNs) have achieved notable success in medical image analysis, though their performance typically relies on large-scale, high-quality labeled datasets. …”
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Urban Surface Water Mapping from VHR Images Based on Superpixel Segmentation and Target Detection by Qingwei Liu, Yugang Tian, Lihao Zhang, Bo Chen

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Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning by Zakwan AlArnaout, Chamseddine Zaki, Yehia Kotb, Mouhammad AlAkkoumi, Nour Mostafa

“…Implementing systems capable of detecting and alerting drivers to drowsiness is therefore essential for accident prevention. …”
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Clinical Features and Value of Tracheal Aspirate Metagenomic Next-Generation Sequencing for Severe Pneumonia in Children in Pediatric Intensive Care Unit by YU XINYAN, LIANG JIUCHAO, YANG RUI, GAI WEI, ZHENG YAFENG

“…Linear discriminant analysis (LDA) effect size (LEfSe) analysis identified that RSV and Streptococcus mitis were the specific species associated with infants. …”
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