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Schedule

Lecture schedule:

block date lecturer content details slides & demos exercise sheets & materials
1 21.04.16 Damian Borth Introduction course formalities, history, definitions, introduction slides -
2 26.04.16 Multimedia Information Systems setup, labels, benchmarking slides sheet
3 03.05.16 Pattern Recognition (supervised) basic decision theory, classification, classifier combination slides Ipython/Jupyter Installation link Ex2IPythonNotebook(right-click and save as ipynb)
4 10.05.16 Pattern Recognition (unsupervised) clustering, dimensionality reduction slides sheet material NumPy Website NumPy Tutorial
5 17.05.16 Text Retrieval document retrieval, retrieval models, relevance feedback, data structures slides -
6 24.05.16 Image Representation 1 definitions, features and their properties, invariance slides live exercise: eye-tracking experiment
7 31.05.16 No lecture - - -
8 07.06.16 Image Representation 2 eye-tracking experiment, global features, local features slides sheet, URL list Caffe Framework Caffe MNIST Tutorial Ex3IPythonNotebook
9 13.06.16 Christian Schulze Similarity Search applications, prototypical architecture, distance measures, object search slides -
10 21.06.16 Damian Borth Visual Recognition and Image Classification 1 applications, challenges, face detection, face recognition, object recognition, visual words slides sheet, material Ex4IPythonNotebook
11 28.06.16 Visual Recognition and Image Classification 2 visual recognition tasks: classification detection, segmentation, Bag-of-Words, SVM slides -
12 05.07.16 Visual Recognition and Image Classification 3 - Deep Learning 1 concept vocabularies, Visual Sentiment Ontology (VSO), SentiBank, CNN Architectures slides sheet, material
13 12.07.16 Deep Learning 2 Neural Networks, End-to-end Learning, AlexNet, Convolutions, Activation, Pooling slides -
14 19.07.16 Christian Schulze Video Analysis Shot Boundary Detection, Keyframe Extraction, Motion, Audio slides -