„scan statistics“

Suchergebnisse

1.000+ Treffer

• Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004–2014: flexibly shaped scan statistics
  Tang, Xianyan ; Geater, Alan ; McNeil, Edward ; Deng, Qiuyun ; Dong, Aihu ; Zhong, Ge
• Neighborhood disparities in stroke and myocardial infarction mortality: a GIS and spatial scan statistics approach
  Pedigo, Ashley ; Aldrich, Tim ; Odoi, Agricola
• A head to head evaluation of 8 biochemical scanning tools for unmeasured ions
  Morgan, Thomas J. ; Anstey, Chris M. ; Wolf, Matthew B.
• Climate Finance as an Instrument to Promote the Green Growth in Developing Countries
  Scandurra, Giuseppe ; Romano, Antonio ; Carfora, Alfonso ; Ronghi, Monica 2018 Springer International Publishing
• Undertaking a randomised controlled trial in the police setting: methodological and practical challenges
  Scantlebury, Arabella ; McDaid, Catriona ; Booth, Alison ; Fairhurst, Caroline ; Parker, Adwoa ; Payne, Rebecca ; Reed, Helen ; Scott, William J. ; Torgerson, David J. ; Hewitt, Catherine
• Prediction of intracranial findings on CT-scans by alternative modelling techniques
  van der Ploeg, Tjeerd ; Smits, Marion ; Dippel, Diederik W. ; Hunink, Myriam ; Steyerberg, Ewout W.
• X-ray fluorescence scanning of discrete samples - a new tool for the geochemical characterization of loess-paleosol sequences
  Profe, Jörn ; Zolitschka, Bernd ; Fuchs, Markus 2018 Staats- und Universitätsbibliothek Bremen
• Book Review: Scan Statistics and Applications, edited by J. Glaz and N. Balakrishnan. A volume in the “Statistics for Industry and Technology” series, Birkhäuser, 1999, ISBN 0-8176-4041-X, 368 pp., 10 illus., $79.95
  Roos, Malgorzata
• Reference values for volumetric capnography-derived non-invasive parameters in healthy individuals
  Tusman, Gerardo ; Gogniat, Emiliano ; Bohm, Stephan H. ; Scandurra, Adriana ; Suarez-Sipmann, Fernando ; Torroba, Agustin ; Casella, Federico ; Giannasi, Sergio ; Roman, Eduardo San
• A New Approach for Sintering Simulation of Irregularly Shaped Powder Particles—Part II: Statistical Powder Modeling
  Weiner, Max ; Zienert, Tilo ; Schmidtchen, Matthias ; Hubálková, Jana ; Aneziris, Christos ; Prahl, Ulrich
• Discovery of under immunized spatial clusters using network scan statistics
  Cadena, Jose ; Falcone, David ; Marathe, Achla ; Vullikanti, Anil
• A stacked ensemble deep learning framework for Alzheimer’s severity ranking and classification using MRI scans
  Pandey, Nidhi ; Sharma, Oshin
• Comprehensive dual framework for lesion segmentation and classification in retinal OCT scans
  Mani, Pavithra ; Ramachandran, Neelaveni ; Paul, Sweety Jose ; Ramesh, Prasanna Venkatesh
• Exploring the scope of deep neural network to predict print densitometry from scanner data
  Debnath, Shankhya ; Chatterjee, Arpitam
• Enhancing the efficiency of lung cancer screening: predictive models utilizing deep learning from CT scans
  Tawfeek, Medhat A. ; Alrashdi, Ibrahim ; Alruwaili, Madallah ; Shaban, Warda M. ; Talaat, Fatma M.
• Simultaneous segmentation and classification of lung CT scans for COVID-19 diagnosis: a deep multi-task learning perspective
  Kordnoori, Shirin ; Sabeti, Maliheh ; Mostafaei, Hamidreza ; Banihashemi, Saeed Seyed Agha
• Accurate segmentation of COVID-19 infected regions in lung CT scans with deep learning
  Lenin Marksia, U. ; Yesubai Rubavathi, C.
• Lung cancer detection from thoracic CT scans using an ensemble of deep learning models
  Gautam, Nandita ; Basu, Abhishek ; Sarkar, Ram
• A teacher-student framework for liver and tumor segmentation under mixed supervision from abdominal CT scans
  Sun, Liyan ; Wu, Jianxiong ; Ding, Xinghao ; Huang, Yue ; Chen, Zhong ; Wang, Guisheng ; Yu, Yizhou
• Detection of COVID-19 from CT scan images: A spiking neural network-based approach
  Garain, Avishek ; Basu, Arpan ; Giampaolo, Fabio ; Velasquez, Juan D. ; Sarkar, Ram