• Produktbild: Computer Vision for Microscopy Image Analysis
  • Produktbild: Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis

157,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

11.12.2020

Herausgeber

Mei Chen

Verlag

Elsevier Science & Technology

Seitenzahl

230

Maße (L/B/H)

23,3/19,2/2 cm

Gewicht

480 g

Sprache

Englisch

ISBN

978-0-12-814972-0

Beschreibung

Portrait

Mei Chen is a principal research manager at Microsoft. She was an associate professor in the Electrical and Computer Engineering Department and director for the Information Science PhD Program at the State University of New York, Albany. She was the founding chair for the Workshop on Computer Vision for Microscopy Image Analysis that has been held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition since 2016. Mei has published extensively in computer vision and biomedical image analysis. Her work was nominated as a finalist for six Best Paper Awards, for which she won three. She earned a PhD in robotics from the School of Computer Science, Carnegie Mellon University, and an MS and BS from Tsinghua University, Beijing, China.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

11.12.2020

Herausgeber

Mei Chen

Verlag

Elsevier Science & Technology

Seitenzahl

230

Maße (L/B/H)

23,3/19,2/2 cm

Gewicht

480 g

Sprache

Englisch

ISBN

978-0-12-814972-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Computer Vision for Microscopy Image Analysis
  • Produktbild: Computer Vision for Microscopy Image Analysis
  • 1. A biologist's perspective on computer vision
    2. Microscopy image formation, restoration and segmentation
    3. Detection and segmentation in microscopy images
    4. Visual feature representation in microscopy image classification
    5. Cell tracking in time-lapse microscopy image sequences
    6. Mitosis detection in biomedical images
    7. Object measurements from 2D microscopy images
    8. Deep learning-based nuclei segmentation and classification in histopathology images with application to imaging genomics
    9. Open data and software for microscopy image analysis