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…image acquisition and resolution to segmentation and cleaning, collect landmarks and semilandmarks, and derive shape variables using Procrustes alignment and sliding procedures. Statistical exercises use principal components and regression to interpret size and shape variation; visualisations include deformations, morphings and heatmaps. Live sessions: 9–13 November, 13:00–18:00 daily, Europe/Madrid (CET, UTC+01:00). Total 30 hours: 25 live plus five independent.

Nov 9–13, 2026

Workshop · Computational Biology

…covers loading, quality control, segmentation, integration, cell typing and identification of cellular neighborhoods and niches. Intended for biomedical and life-science graduates or postgraduates with some R experience; demonstrations use R and Python code is also supplied. Familiarity with RNA sequencing is helpful. Sessions on 1

Feb 1–5, 2027

Workshop · Bio-Informatics

…reconstruction, preprocessing and segmentation, including advanced and AI-assisted methods. Practical work improves segmented three-dimensional meshes, reduces noise and prepares datasets for quantitative analysis, images and video. It provides a technical foundation for beginners working with biological or earth-science specimens. Live sessions: 14, 16, 19, 21 and 23 October, 14:00–18:30, Europe/Madrid (CEST, UTC+02:00). Total 25 hours, i

Oct 14–23, 2026

Workshop · Image Processing

STED microscopy reveals dendrite-specificity of spines

Jan Knobloch, Gilles Laurent, Marcel Lauterbach · FENS Forum 2024

…of skeletonization in 3D and segmentation of almost 7000 spines allowed us to describe their morphology in detail. To classify the spines, we clus

ePoster · Neuroscience

Crowding and the Architecture of the Visual System

Adrien Doerig · Laboratory of Psychophysics, BMI, EPFL

Classically, vision is seen as a cascade of local, feedforward computations. This framework has been tremendously successful, inspiring a wide range of ground-breaking findings in neuroscience and computer vision. Recently, feedforward Convolutional Neural Networks (ffCNNs), inspired by this classic framework, have revolutionized computer vision and been adopted as tools in neuroscience. However, despite these successes, there is much more to vision. I will present our work using visual crowding and related psychophysical effects as probes into visual processes that go beyond the classic fra

Wed, Dec 2, 2020 · 12:15 UTC

Seminar · Vision Science