Hi everyone

Instats is excited to offer a 1-day seminar, AI-Powered Image Analysis,
livestreaming December 2 and led by Nikolay Oskolkov, Group Leader (PI) at
LIOS. Digital morphology, camera trap data, and automated phenotyping
generate massive datasets that demand automated, quantitative workflows,
and this intensive workshop equips you to turn raw images into rigorously
validated results. Beginning with the theoretical foundations of
convolutional neural networks, you'll learn how to harness transfer
learning, UNet segmentation, Mask R-CNN instance delineation, and
object-detection pipelines, while integrating classical OpenCV techniques
for hybrid solutions. Nikolay will demonstrate end-to-end coding in
Jupyter, using ChatGPT to accelerate development of reproducible Python
scripts, data loaders, augmentation routines, training loops, and
evaluation dashboards. Special attention is given to Bayesian uncertainty
estimation, GRAD-CAM interpretability, and robust benchmarking so that your
analyses meet peer-review standards and are ready for theses, grant
applications, and high-impact publications. By the end of the day you will
be able to design, implement, and critique complete image-analysis
experiments: splitting datasets to control batch effects, fine-tuning
models on small domain-specific collections, measuring fossils, phenotypes,
or species interactions, and documenting every step for transparent sharing.

https://instats.org/seminar/ai-powered-image-analysis

Sign up today to secure your spot, and feel free to share this opportunity
with colleagues and students who might benefit!

Best wishes

Michael Zyphur
Professor and Director
Instats | instats.org

Michael Zyphur <mzyphur@instats.org>

(to subscribe/unsubscribe the EvolDir send mail to
golding@mcmaster.ca)