Efficient tree mapping through deep distance transform (DDT) learning by Jan Schindler, Ziyi Sun, Bing Xue, Mengjie Zhang

“…While previous methods had to combine multi-model and multi-task outputs to create decision surfaces, we developed an efficient UNet-based modelling approach which focusses solely on learning the distance transforms of tree objects as cost surface for watershed segmentation. Our algorithm achieves superior instance segmentation across native forest, rural and urban environments in Aotearoa New Zealand, with an overall F1 score of 0.53 — 0.18 for small, 0.45 for medium and 0.67 for large crowns — surpassing previous approaches while decreasing modelling complexity, enabling fast and large-scale tree mapping.…”
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Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples by Mark Höller, Kay-M. Otto, Uwe Klose, Samuel Groeschel, Hans-H. Ehricke

“…This allows two- and three-dimensional LIC maps to be generated, depicting fiber structures with excellent contrast, even in regions of crossing and branching fibers. …”
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Mapping the Epidemiologic Features of Endotracheal Tube ObstructionTake-Home Points by Vimal Bhardwaj, MD, FNB(Critical Care), EDIC, Abhishek Samprathi, MD, DrNB, EDIC, Manu M.K. Varma, MD, DM, Kingshuk Saha, MSc, Ross Prager, MD, John Basmaji, MD, Nicolas Orozco, MD, Srirang Ramamoorthy, MSc, Jose Chacko, MD, EDIC, Arjun Alva, MD

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Optogenetic mapping of feeding and self-stimulation within the lateral hypothalamus of the rat. by Kevin R Urstadt, Kent C Berridge

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Mapping clay fraction oxides in Brazil using Earth observation strategy by Jorge Tadeu Fim Rosas, José A.M. Demattê, Nícolas Augusto Rosin, Raul Roberto Poppiel, Nélida E.Q. Silvero, Merilyn Taynara Accorsi Amorim, Heidy S. Rodríguez-Albarracín, Letícia Guadagnin Vogel, Bruno dos Anjos Bartsch, José João Lelis Leal de Souza, Lucas de Carvalho Gomes, Danilo César de Mello

“…A dataset, comprising 5,330 sites (0–20 cm and 80–100 cm) across all 27 states was employed in prediction. Six spectral variables obtained from the historical Landsat series (bare soil) and seven terrain attributes derived from a digital elevation model were employed to generate the Fe2O3, Al2O3, and SiO2 maps, using the Random Forest algorithm. …”
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The ethics of data interoperability: Mapping problems and strategies in biomedical data and beyond by Asher Brandon Caplan, Colin Koopman

“…However, interoperability poses a number of ethical problems whose contours can prove especially challenging in comparison to how ethical harms take hold at other moments of the data life cycle (such as algorithmic processing or results dissemination). Taking biomedical data interoperability as a focal domain, this article provides an overview of data interoperability, maps the central ethical harms that may challenge interoperability projects, and proposes a response to these problems through an approach rooted in philosophical pragmatism. …”
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Rapid literature mapping on the recent use of machine learning for wildlife imagery by Nakagawa, Shinichi, Lagisz, Malgorzata, Francis, Roxane, Tam, Jessica, Li, Xun, Elphinstone, Andrew, Jordan, Neil R., O'Brien, Justine K., Pitcher, Benjamin J., Van Sluys, Monique, Sowmya, Arcot, Kingsford, Richard T.

“…Through a literature survey (a ‘rapid’ review) and bibliometric mapping, we explored its use across: 1) species (vertebrates), 2) image types (e.g., camera traps, or drones), 3) study locations, 4) alternative machine learning algorithms, 5) outcomes (e.g., recognition, classification, or tracking), 6) reporting quality and openness, 7) author affiliation, and 8) publication journal types. …”
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Risk Prediction Score for Thermal Mapping of Pharmaceutical Transport Routes in Brazil by Clayton Gerber Mangini, Nilsa Duarte da Silva Lima, Irenilza de Alencar Nääs

“…The current research focused on creating a model to assess risk levels and predict risk categorization (low, moderate, and high) associated with thermal mapping across pharmaceutical transportation pathways. …”
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Mapping the use of artificial intelligence in medical education: a scoping review by Erwin Hernando Hernández Rincón, Daniel Jimenez, Lizeth Alexandra Chavarro Aguilar, Juan Miguel Pérez Flórez, Álvaro Enrique Romero Tapia, Claudia Liliana Jaimes Peñuela

“…Abstract Introduction The integration of artificial intelligence (AI) in healthcare has transformed clinical practices and medical education, with technologies like diagnostic algorithms and clinical decision support increasingly incorporated into curricula. …”
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Residual Stresses of Small-Bore Butt-Welded Piping Measured by Quantum Beam Hybrid Method by Kenji Suzuki, Yasufumi Miura, Hidenori Toyokawa, Ayumi Shiro, Takahisa Shobu, Satoshi Morooka, Yuki Shibayama

“…Furthermore, to obtain detailed residual stresses near the penetration bead where the maximum stress is generated, the residual stresses near the inner surface of the weld were measured using the double-exposure method (DEM) with hard X-rays of synchrotron radiation. A method using a cross-correlation algorithm was proposed to determine the accurate diffraction angle from the complex diffraction patterns from the coarse grains, dendritic structures, and plastic zones. …”
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High-Radix Taylor-Optimized Tone Mapping Processor for Adaptive 4K HDR Video at 30 FPS by Xianglong Wang, Zhiyong Lai, Lei Chen, Fengwei An

“…However, real-time processing of HDR content remains challenging due to the computational complexity of tone mapping algorithms and the inherent limitations of Low Dynamic Range (LDR) capture systems. …”
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Simulating non-completely positive actions via exponentiation of Hermitian-preserving maps by Fuchuan Wei, Zhenhuan Liu, Guoding Liu, Zizhao Han, Dong-Ling Deng, Zhengwei Liu

“…This algorithm acts as a building block of large-scale quantum algorithms and presents a pathway for exploring potential quantum speedups across a wide range of information-processing tasks.…”
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Using Dendritic Heat Maps to Simultaneously Display Genotype Divergence with Phenotype Divergence. by Matthew Kellom, Jason Raymond

“…We demonstrate that dendritic heat maps give freedom to scrutinize specific clustering levels across a range of cutoffs, track changes in phenotype inequity across multiple levels of sequence clustering specificity, and easily visualize how deeply rooted changes in phenotype inequity are in a dataset. …”
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Efficient search, mapping, and optimization of multi‐protein genetic systems in diverse bacteria by Iman Farasat, Manish Kushwaha, Jason Collens, Michael Easterbrook, Matthew Guido, Howard M Salis

“…Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi‐protein expression space across a > 10,000‐fold range with tailored search parameters and well‐predicted translation rates. …”
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Blending physical and artificial intelligence models to improve satellite-derived bathymetry mapping by Daniel García-Díaz, Sandra Paola Viaña-Borja, Mar Roca, Gabriel Navarro, Isabel Caballero

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An improved height sampling approach used for global urban building height mapping by Tingting He, Yihua Hu, Fashuai Li, Yuwei Chen, Maoxin Zhang, Qiming Zheng, Baiyu Dong, He Ren

“…Several height products developed across different spatial scales, yet challenges remain due to the spatial and temporal incompleteness of publicly available building height samples, which introduce inherent uncertainties in global height mapping. …”
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High‐resolution mapping of cancer cell networks using co‐functional interactions by Evan A Boyle, Jonathan K Pritchard, William J Greenleaf

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Cluster mapping in Spain: Exploring the correlation between industrial agglomeration and regional performance by Rudy Fernández Escobedo, Begoña Eguía Peña, Leire Aldaz Odriozola

“…A six-step methodology is applied departing from cross-industry linkages and implementing clustering algorithms; one set of clusters is elected and mapped over territory. …”
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dmQAR: Mapping Metacognition in Digital Spaces onto Question–Answer Relationship by Brittany Adams, Nance S. Wilson, Gillian E. Mertens

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Methodological Integration of Machine Learning and Geospatial Analysis for PM10 Pollution Mapping by Kalid Hassen Yasin, Muaz Ismael Yasin, Anteneh Derribew Iguala, Tadele Bedo Gelete, Erana Kebede

“…The study contributes valuable insights for implementing scalable pollution prediction systems in resource-constrained urban environments while acknowledging interpretability challenges inherent to complex ML models. • Preprocessing of spatial data from various sources, incorporating the handling of missing/abnormal data, analysis, and normalization • Implementation of the three ML algorithms with rigorous hyperparameter tuning, model validation, and performance assessment • Mapping PM10 Hotspots on the Gradient Direction and Distance from the City Center…”
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