Precise Foot Feature Point Localization and Automatic Parameters Measurement by JI Mian, LIN Yanping, WANG Dongmei, CHEN Li, MA Xin

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Machine Learning in Ambient Assisted Living for Enhanced Elderly Healthcare: A Systematic Literature Review by Aabid A. Mir, Ahmad S. Khalid, Shahrulniza Musa, Mohammad Faizal Ahmad Fauzi, Normy Norfiza Abdul Razak, Tong Boon Tang

“…This systematic literature review (SLR) explores the current state and advancements in AAL technologies, with a specific focus on their applications in elderly care. It synthesizes current methodologies, including predictive analytics, Explainable AI (XAI), and Generative AI (GenAI), while also evaluating the role of vision-based systems and multi-modal data fusion. …”
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An approach to forecasting damage due to unfavorable circumstances associated with indistinguishability of source data by V. F. Zolotukhin, A. V. Matershev, L. A. Podkolzina

“…The efficiency of predicting damage to complex systems depends directly on the quality of processing methods, systematization, and the amount of input data. …”
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Neuroscience-informed nomogram model for early prediction of cognitive impairment in Parkinson's disease by Sudharshan Putha, Swaroop Reddy Gayam, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka, Sateesh Kumar Nallamala, Praveen Thuniki

“…Subsequently, these variables were integrated into a visualized nomogram model to facilitate early prediction of cognitive impairment (CI) risk. Performance evaluation of the model demonstrated high accuracy, consistency, and clinical applicability, significantly enhancing diagnostic efficiency for neurologists. …”
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Mapping the Research Landscape of Agricultural Sciences by Dmitry Devyatkin, Elena Nechaeva, Roman Suvorov, Ilya Tikhomirov

“… A research landscape is a high-level description of the current state of a certain scientific field and its dynamics. High-quality research landscapes are important tools that allow for more effective research management. …”
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Vehicular-Computational Resource Geofencing: Efficient Spatiotemporal Uncertainty Estimation by Ghada Afifi, Bassem Mokhtar

“…However, existing VCC solutions are unable to satisfy the stringent quality of experience (QoE) requirements for running vehicular applications, especially delay- and throughput-sensitive applications, given the high communication delay and latency with the central cloud. …”
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Coffee-Leaf Diseases and Pests Detection Based on YOLO Models by Jonatan Fragoso, Clécio Silva, Thuanne Paixão, Ana Beatriz Alvarez, Olacir Castro Júnior, Ruben Florez, Facundo Palomino-Quispe, Lucas Graciolli Savian, Paulo André Trazzi

“…The evaluation of the models included quantitative and qualitative analyses, considering the mAP, F1-Score, and recall metrics. …”
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Detection of Wild Mushrooms Using Machine Learning and Computer Vision by Christos Chaschatzis, Chrysoula Karaiskou, Chryssanthi Iakovidou, Panagiotis Radoglou-Grammatikis, Stamatia Bibi, Sotirios K. Goudos, Panagiotis G. Sarigiannidis

“…The proposed approach utilises unmanned aerial vehicles (UAVs) equipped with multispectral imaging and the YOLOv5 object detection algorithm. A custom dataset, the wild mushroom detection dataset (WOES), comprising 907 annotated aerial and ground images, was developed to support model training and evaluation. …”
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Harnessing dual variational autoencoders to decode microbe roles in diseases for traditional medicine discovery by Qing Ye, Yaxin Sun, Yaxin Sun, Yaxin Sun

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Deep learning-based object detection and robotic arm grasping by ZHANG Lei, ZHANG Senhui, YAN Song, YUAN Yuan

“…Additionally, the integration of a parameter-free three-dimensional attention mechanism enabled the network to focus more on grasping information features and suppress background noise. Finally, a grasping quality evaluation was employed to refine the grasping boxes, and the grasping box with the highest confidence score was output. …”
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Simulation and Modelling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin by Prasunika Khare, Nelson Costa, Marc Ruiz, Antonio Napoli, Jaume Comellas, Joao Pedro, Luis Velasco

“…In view of that, the fourth-order Runge–Kutta in the interaction picture (RK4IP) method, complemented with an adaptive step size algorithm to further reduce the computation time, is evaluated as an alternative to reduce time complexity. …”
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Rate-Adaptive LiDAR Point Cloud Streaming Over LEO Satellite Networks by Dominic Laniewski, Nils Aschenbruck

“…We develop a novel, real-time capable rate-adaptation algorithm leveraging Google Draco. It predicts optimal encoding parameters for each mini point cloud to maximize the point cloud quality under varying network conditions. …”
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Protecting vulnerable people during pandemics through home delivery of essential supplies: a distribution logistics model by Eric Breitbarth, Wendelin Groβ, Alexander Zienau

“…The purpose of this paper is to evaluate feasible and resource-efficient home delivery strategies, including collaboration between retailers and logistics service providers based on a practical application. …”
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Multi-label semantic segmentation of magnetic resonance images of the prostate gland by Mark Locherer, Christopher Bonenberger, Wolfgang Ertel, Boris Hadaschik, Kristina Stumm, Markus Schneider, Jan Philipp Radtke

“…Although we trained on tiny datasets our method achieves excellent segmentation quality and is even able to detect prostate cancer. …”
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Feasibility of Implementing Motion-Compensated Magnetic Resonance Imaging Reconstruction on Graphics Processing Units Using Compute Unified Device Architecture by Mohamed Aziz Zeroual, Natalia Dudysheva, Vincent Gras, Franck Mauconduit, Karyna Isaieva, Pierre-André Vuissoz, Freddy Odille

“…Across all datasets, the normalized root mean square error (NRMSE) remained on the order of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>6</mn></mrow></msup></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>4</mn></mrow></msup></semantics></math></inline-formula>, indicating that the CUDA-accelerated method preserved image quality. Furthermore, a roofline analysis was conducted to quantify the kernel’s performance on one of the evaluated datasets. …”
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Quantitative comparison of a novel swept-source optical coherence tomography angiography device with three established systems by Michael Hafner, Siegfried G. Priglinger, Bettina von Livonius, Maximilian J. Gerhardt

“…These findings suggest that DREAM OCT is a promising tool for deep retinal imaging, with strong potential for clinical application and research.…”
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The diagnostic and prognostic capability of artificial intelligence in spinal cord injury: A systematic review by Saran Singh Gill, Hariharan Subbiah Ponniah, Sho Giersztein, Rishi Miriyala Anantharaj, Srikar Reddy Namireddy, Joshua Killilea, DanieleS.C. Ramsay, Ahmed Salih, Ahkash Thavarajasingam, Daniel Scurtu, Dragan Jankovic, Salvatore Russo, Andreas Kramer, Santhosh G. Thavarajasingam

“…Method: ology: The primary aim was to evaluate the performance of AI algorithms in diagnosing and prognosticating tSCI. …”
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Building health systems capable of leveraging AI: applying Paul Farmer’s 5S framework for equitable global health by Liam G. McCoy, Azra Bihorac, Leo Anthony Celi, Matthew Elmore, Divya Kewalramani, Teddy Kwaga, Nicole Martinez-Martin, Renata Prôa, Joel Schamroth, Jonathan D. Shaffer, Alaa Youssef, Amelia Fiske

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Comparison of Electronic Surveillance With Routine Monitoring for Patients With Lymphoma at High Risk of Relapse: Prospective Randomized Controlled Phase 3 Trial (Sentinel Lymphoma... by Katell Le Dû, Adrien Chauchet, Sophie Sadot-Lebouvier, Olivier Fitoussi, Bijou Fontanet, Arnaud Saint-Lezer, Frédéric Maloisel, Cédric Rossi, Sylvain Carras, Anne Parcelier, Magali Balavoine, Anne-Lise Septans

“…We evaluated the effect of a web-mediated follow-up application for patients with lymphoma at high risk of relapse. …”
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Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions by Elif Yavuz, Alihan Öztürk, Nedime Gaye Nur Balkanlı, Şeref Naci Engin, S. Levent Kuzu

“…Machine learning has significantly advanced traffic surveillance and management, with YOLO (You Only Look Once) being a prominent Convolutional Neural Network (CNN) algorithm for vehicle detection. This study utilizes YOLO version 7 (YOLOv7) combined with the Kalman-based SORT (Simple Online and Real-time Tracking) algorithm as one of the models used in our experiments for real-time vehicle identification. …”
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