Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization by Awais Khan, Jung-Yeon Kim, Chomyong Kim, Muhammad Attique Khan, Hyojin Shin, Jiyoung Woo, Yunyoung Nam

“…The 7-RBNet and 9-RBNet self-attention models demonstrated superior accuracy and precision rates, leading us to exclude the 3-RBNet self model from further analysis. To optimize feature selection and improve classification performance while reducing computational costs, we employed the tree seed algorithm on the self-attention features of 7-RBNet and 9-RBNet self-attention models. …”
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Retinal fundus imaging-based diabetic retinopathy classification using transfer learning and fennec fox optimization by Indresh Kumar Gupta, Shruti Patil, Supriya Mahadevkar, Ketan Kotecha, Awanish Kumar Mishra, Joel J.P.C. Rodrigues

“…Elevated blood glucose levels damage the retina's microvasculature, initiating the condition. Early detection through retinal fundus imaging, supported by timely analysis and treatment, is critical for managing DR effectively. …”
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Secure Indoor Water Level Monitoring with Temporal Super-Resolution and Enhanced Yolov5 by Sui Guo, Jiazhi Huang, Yuming Yan, Peng Zhang, Benhong Wang, Houming Shen, Zhe Yuan

“…This module processes low-resolution water-level images to generate high-resolution outputs, thereby enabling reliable detection even in suboptimal conditions. Furthermore, unlike existing complex model-based approaches, our enhanced, lightweight Yolov5 model, featuring a small-scale feature mapping branch, ensures real-time monitoring and accurate detection across a variety of conditions, including daytime, nighttime, misty conditions, and wet surfaces. …”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm by K. Gopalakrishnan, R. Sivaraj, M. Vijayakumar

“…Deep learning (DL) based object detection model has been carried out in numerous applications. …”
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Integrating non-linear radon transformation for diabetic retinopathy grading by Farida Mohsen, Samir Belhaouari, Zubair Shah

“…These results demonstrate RadFuse’s capacity to capture complex non-linear features, advancing diabetic retinopathy classification and promoting the integration of advanced mathematical transforms in medical image analysis. …”
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Gas concentration prediction in photoacoustic spectroscopy using PSO-EAP-CNN to address correlation degradation by Zhanshang Su, Pengpeng Wang, Zhengzhuo Li, Yawen Li, Tianxiang Zhao, Yujie Duan, Fupeng Wang, Cunguang Zhu

“…This work advances PAS-based gas detection, offering enhanced accuracy and noise resilience for practical trace gas analysis.…”
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Histological Fixation Process and Fixatives by Tuğba Dağdeviren, Hatice Kübra Yolcu, Bülent Ünver

“…Detection solutions are classified in terms of content. …”
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Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study by Wenting Feng, Wen Zhang, Yan Guo, Naixing Zhang, Liang Zhou, Dafeng Lin, Linlin Chen, Caiping Li, Liuwei Shi, Xiangli Yang, Peimao Li, Dianpeng Wang

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Serum metabolite and metal ions profiles for breast cancer screening by Wojciech Wojtowicz, R. Tarkowski, A. Olczak, A. Szymczycha-Madeja, P. Pohl, A. Maciejczyk, Ł. Trembecki, R. Matkowski, Piotr Młynarz

“…Quantified relative integrals allowed for discrimination between studied subgroups, validated with a holdout set. Feature importance and statistical analysis for metabolomics and metallomics extracted a set of common entities which in combination provides valuable insights into ongoing molecular disturbances and disease progression.…”
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A Novel Correspondence Model for Linking Objects and Texts in Construction Plans by S. Hong, S. Landgraf, M. Hillemann, M. Ulrich

“…Leveraging deep-learning-based object detection and text recognition techniques, our model establishes semantic correspondences between visual and textual elements. …”
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A correlation study on EEG signals during visual concentration test and clinical evaluation in schizophrenia patients by Min-Wei Huang, Qun-Wei Chang, Wen-Lin Chu

“…Results The study successfully demonstrated the potential of a concentration detection system, integrating EEG signal analysis with PANSS scores, to classify schizophrenia severity accurately. …”
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A Predictive Model for Perinatal Brain Injury Using Machine Learning Based on Early Birth Data by Ga Won Jeon, Yeong Seok Lee, Won-Ho Hahn, Yong Hoon Jun

“…Additionally, SHAP analysis showed that LDH levels had the highest SHAP values. …”
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Transferable deep learning with coati optimization algorithm based mitotic nuclei segmentation and classification model by Amal Alshardan, Nazir Ahmad, Achraf Ben Miled, Asma Alshuhail, Yazeed Alzahrani, Ahmed Mahmud

“…These computer-aided techniques are aimed at detecting the attentive biological markers for assisting the final cancer grading. …”
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Spatial–Frequency Fusion Network With Learnable Fractional Fourier Transform for Remote Sensing Imaging Enhancement by Wenyu Xu, Maohan Liang, Yuxu Lu, Ruobin Gao, Dong Yang

“…Furthermore, an attentive frequency gate selectively emphasizes critical frequency features based on the local features of the input image. …”
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MHAGuideNet: a 3D pre-trained guidance model for Alzheimer’s Disease diagnosis using 2D multi-planar sMRI images by Yuanbi Nie, Qiushi Cui, Wenyuan Li, Yang Lü, Tianqing Deng

“…The model utilizes a pre-trained 3D convolutional neural network to direct the feature extraction of multi-planar 2D slices, specifically targeting the detection of features like structural atrophy. …”
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FARVNet: A Fast and Accurate Range-View-Based Method for Semantic Segmentation of Point Clouds by Chuang Chen, Lulu Zhao, Wenwu Guo, Xia Yuan, Shihan Tan, Jing Hu, Zhenyuan Yang, Shengjie Wang, Wenyi Ge

“…This paper presents FARVNet, a novel real-time Range-View (RV)-based semantic segmentation framework that explicitly models the intrinsic correlation between intensity features and spatial coordinates to enhance feature representation in point cloud analysis. …”
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Knowledge-Driven Flood Intelligent Monitoring (KDFIM) Method: Analyzing the Kakhovka Dam Destruction Incident by Zhijun Jiao, Zhimei Zhang, Biyan Chen, Syed Amer Mahmood, Lixin Wu

“…First, KDFIM integrates both satellite imaging knowledge and ground object scattering knowledge to construct a spatiotemporal SAR feature fusion module, which is designed to mitigate the noise and interference present in the background and to extract multispectral SAR features for flood detection. …”
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Interference of SARS-CoV-2 with other Respiratory Viral Infections agents during Pandemic by A. A. Sominina, D. M. Danilenko, K. A. Stolyarov, L. S. Karpova, M. I. Bakaev, T. P. Levanyuk, E. I. Burtseva, D. A. Lioznov

“…The increase of COVID-19 activity in the fall of 2020 began from week 41 with the peak (26.6–31.3%) of detection in the period from the week 47.2020 to week 4. 2021. …”
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Genomic characteristics of monkeypox virus from 8 cases in Changning District， Shanghai by HE Xiaoding, XU Yang, YIN Ning, WANG Zhenyu, GUO Jiayin

“…The detection rates of vesicle fluid and anal swabs for MPXVs are significantly higher than that of throat swabs.…”
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A Method for Aileron Actuator Fault Diagnosis Based on PCA and PGC-SVM by Wei-Li Qin, Wen-Jin Zhang, Chen Lu

“…Second, the data feature extraction is performed with dimension reduction using PCA. …”
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