INB LUNCH-SEMINAR - Vorträge

 

Aufgrund der aktuellen COVID-19 Situation derzeit nur online via WEBEX:

https://uni-luebeck.webex.com/meet/thomas.martinetz

 

Das Seminar findet freitags 12:00 Uhr s.t. statt und dient der

  1. Darstellung und Diskussion von aktuellen wissenschaftlichen Themen
  2. Vorstellung von Ergebnissen aus Bachelor- und Masterarbeiten.  

 

Die derzeitige Terminplanung ist in der folgenden Tabelle zusammengefasst:

DATUM VORTRAGENDE THEMA DES VORTRAGS
14.1.2022 Christian Thiemann Overinterpretation reveals image classification model pathologies
21.1.2022 Alexandra Korda Fractal dimension of brain sMRI in first-episode and clinical high-risk patients
28.1.2022 Benjamin Coors Incorporating Prior Knowledge of Invariances into Deep Models for Computer Vision
11.2.2022 Lars Scharje A data-centric approach for improving ambiguous labels
18.2.2022 Christoph Linse Application of handcrafted filters in Convolutional Neural Networks
25.2.2022 Thomas Käster Self-Supervised Learning with Barlow Twins
4.3.2022 Celina Schubbe Body Part Segmentation on RGB-D Images
11.3.2022 Lennart Berkel Collimation Adjustment in X-Ray Diagnostics using Deep Learning
25.3.2022 Manuel Laufer & Dominik Mairhöfer The Current State of the X-Ray Assistent
1.4.2022 Philipp Grüning Architecture Search for Deep Networks
8.4.2022 Marius Jahrens Graph Neural Networks
6.5.2022 Erhardt Barth The OptiVisT project and recognition in videos
13.5.2022 Muhammad Mushtaq Cortical stimulation effects on sleep spindles during NREM sleep
20.5.2022 Hans-Oliver Hansen Self-supervised Learning
3.6.2022 Hajo Nils Krabbenhöft German Speech Recognition – Build your own State of the Art
1.7.2022 Amir Madany The DREAM Olfaction Prediction Challenge
8.7.2022 Marvin Raasch Automatische Winkel-Quantifizierung der Sylvischen Furche in standardisierten Ultraschallbildern der vorderen koronalen Ebenen durch Deep Learning"
     
tba Thomas Martinetz  
tba Kai Labusch  
tba Christian Thiemann  
tba Christoph Linse  
tba Thomas Käster  
tba Manuel Laufer  
tba Dominik Mairhöfer  
tba Philipp Grüning  
tba Marius Jahrens  
2021 VORTRAGENDE THEMA DES VORTRAGS
5.3.2021 Hans-Oliver Hansen, M.Sc. Deep Image Priors
19.3.2021 Dr. Thomas Käster / Christoph Schlichting, B.Sc. Multi-Label Image Recognition
26.3.2021 Christoph Linse, M.Sc. COVID-Nets: Deep CNN Architectures for Detecting COVID-19 from Chest CT Scans
9.4.2021 Manuel Laufer, M.Sc. ToF Cameras for Quality Assessment of Ankle Positioning
23.4.2021 Dominik Mairhöfer, M.Sc. Diagnostic Quality Assessment of Ankle Radiographs
7.5.2021 Muhammad Mushtaq, M.Sc. Thalamocortical model for slow oscillations
21.5.2021 Marius Jahrens, M.Sc. Generalized Architecture Search and Architecture Learning
28.5.2021 Philipp Grüning, M.Sc. FP-nets and Vision
4.6.2021 Prof. Dr. Erhardt Barth / Philipp Grüning, M.Sc. FP-nets and Hyper-Selectivity
11.6.2021 PD Dr. Amir Madany Deep Learning in Higher Education
9.7.2021 Prof. Dr. Thomas Martinetz Generalization of over-parameterized classifiers
23.7.2021 Christian Thiemann, M.Sc. Automatische Detektion monoklonaler Banden bei Immunfixationselektrophorese
6.8.2021 Hans-Oliver Hansen, M.Sc. Hopfield-Layer
20.8.2021 Prof. Dr. Thomas Martinetz Neural Tangent Kernels
3.9.2021 Dr. Thomas Käster Meta Pseudo Labels
24.9.2021 Christoph Linse, M.Sc. A walk in the blackbox - 3D visualization methods for CNNs
1.10.2021 Manuel Laufer, M.Sc. Generating synthetic depth images from CT data
8.10.2021 Dominik Mairhöfer, M.Sc. Spatial Transformer Networks for Spatial Attention
22.10.2021 Muhammad Mushtaq, M.Sc. Slow oscillations and sleep spindles in human sleep study
29.10.2021 Marius Jahrens, M.Sc. DINO: Emerging Properties in Self-Supervised Vision Transformers
5.11.2021 Philipp Grüning, M.Sc. Graph Neural Networks for Asthma Classification
12.11.2021 Prof. Dr. Erhardt Barth The Riemann Machine
3.12.2021 Hans-Oliver Hansen, M.Sc. Vision Transformer, MLP-Mixer und ConvMixer
10.12.2021 Norman Scheel, PhD Neuroimaging of aging, dementia, and Alzheimer’s Disease
17.12.2021 PD Dr. Amir Madany