BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.4.0.1//EN TZID:Europe/Paris X-WR-TIMEZONE:Europe/Paris BEGIN:VEVENT UID:316@isdm.umontpellier.fr DTSTART;TZID=Europe/Paris:20230615T140000 DTEND;TZID=Europe/Paris:20230615T140000 DTSTAMP:20260828T082144Z URL:https://isdm.umontpellier.fr/events/multi-scale-image-analysis-for-pla nt-phenotyping/ SUMMARY:Multi-scale image analysis for plant phenotyping DESCRIPTION:Room 109\, Building 9\, St Eloi campus\n\nMachine Learning in M ontpellier\, Theory &\; Practice\n\nFood sovereignty challenges in the South are occurring in an increasingly uncertain environment of geopolitic al instability and climate change threat. This situation calls for the dev elopment of sustainable and resilient food production systems. In this con text\, modelling\, image analysis\, and high-throughput observation system s have become ubiquitous in agronomy to monitor and simulate the performan ce of agricultural systems. In this presentation\, I will present the acti vities of the Phenomen team in image analysis of plants observed at scales ranging from nanometers to kilometers\, using registration\, geostatistic s\, segmentation\, and time-lapse tracking techniques. The core of the pre sentation will focus on segmentation and time-lapse tracking of root archi tectures. With its simple geometry but complex topology\, this problem eff iciently resists deep-learning approaches\; recently\, we studied this sub ject and contributed to the state of the art by rethinking "\;traditio nal"\;"\; pipelines based on deep learning [1]. The talk will conc lude with a discussion to suggest ways to go beyond the state of the art b y considering a new formalization of the problem leveraging recent deep-le arning techniques for image\, graphs\, and time-lapse tracking."\;\n\n Machine Learning in Montpellier\, Theory &\; Practice ATTACH;FMTTYPE=image/jpeg:https://isdm.umontpellier.fr/wp-content/uploads/ 2026/06/ml-mtp-gC78d5.png CATEGORIES:ML MTP LOCATION:Saint Eloi Campus\, Building 9\, Room 109\, Montpellier\, X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Montpellier\, ;X-APPLE-RADI US=100;X-TITLE=Saint Eloi Campus\, Building 9\, Room 109:geo:0,0 END:VEVENT BEGIN:VTIMEZONE TZID:Europe/Paris X-LIC-LOCATION:Europe/Paris BEGIN:DAYLIGHT DTSTART:20230326T030000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST END:DAYLIGHT END:VTIMEZONE END:VCALENDAR