6th IPPN Imaging webinar: Ian Stavness - Deep Learning Approaches for Image Segmentation and Object Counting in Plant Phenotyping

    

The next IPPN Imaging webinar will take place this Friday June 22th at 15:00 (CEST).

The 6th presenter is Ian Stavness, University of Saskatchewan.  Moderator: Daniel Pflugfelder
Title: Deep Learning Approaches for Image Segmentation and Object Counting in Plant Phenotyping

 

The topic is linked to the upcoming deadline for the CVPPP 2018 call for abstracts: https://www.plant-phenotyping.org/CVPPP2018

 

Join the meeting online this Friday at: join.me/plant-phenotyping at 15.00 CEST.

Check when the webinar is held in your time zone: https://join.me/timezone/1529672400000/1529676000000

Conference ID:  536-399-875 #

 

Presenter:

Ian Stavness, PhD
Associate Professor
Computer Science 
University of Saskatchewan
http://www.cs.usask.ca/faculty/stavness/

Bio:
Dr. Ian Stavness is an Associate Professor in Computer Science at the University of Saskatchewan. He leads the image and data analysis group for the Plant Phenotyping and Imaging Research Centre (P2IRC) at the University of Saskatchewan. He also directs the Biomedical Imaging & Graphics (BIG) lab focused on 3D modeling, image analysis and deep learning for biological and biomedical applications. Ian is an OpenSim Fellow in neuro-musculoskeletal modeling and simulation and its translation to rehabilitation medicine. He completed a post-doc at Stanford University with Scott Delp at the NIH Center for Biomedical Computation and his PhD on 3D biomechanical simulation at the University of British Columbia in 2011. 

 

Abstract: Image-based plant phenotyping is being rapidly adopted in plant physiology and plant breeding research. Extracting phenotypic information from images of plants and crops remains a core challenge for the field. Deep learning approaches have shown promising initial results for meeting the challenge, particularly for outdoor images of plant and crops that are captured under highly variable conditions in terms of lighting, wind, and ground background. In this talk, I will present our submission to the 2017 CVPPP Leaf Counting Competition that involved convolutional neural networks for segmenting plant from background and for counting the number of leaves on rosettes. I will also discuss recent work applying similar techniques to outdoor images of crops.

 

Learn more about the IPPN Imaging Working Group.

 

Enjoy this webinar,

 The IPPN Imaging steering committee:

Co-Chair: Tony Pridmore, University of Nottingham, UK

Co-Chair: Hanno Scharr, IBG-2, Forschungszentrum Jülich, Germany

Rick van de Zedde, Wageningen UR, The Netherlands

Sotirios Tsaftaris, University of Edinburgh, UK

Scott Chapman, CSIRO, Australia