Table of Contents




Welcome to the course website for “Multimedia Data Mining” SoSe 2018! This lecture gives an introduction to social multimedia processing and extracting information from images, videos, and other multimedia content. The focus will be on retrieval, search, and filtering of concepts, objects, and scenes.

  • Lecturers: Dr. Damian Borth, Prof. Andreas Dengel, and guest lecturer (Dr. Christian Schulze and Marco Schreyer)
  • Credits: 2C+1R, 4 credit points
  • Language: English
  • Level: Master (entry level)
  • Requirements
    • Introduction to Pattern Recognition (recommended, but not required)
    • Introduction to Image Processing and Image Understanding (recommended, but not required)
    • basic probability theory and analysis
  • Literature (available in computer science library):
    • Ian Goodfellow, Yoshua Bengio,Aaron Courville: Deep Learning, 2017
    • Duda, Hart, Stork: Pattern Classification, 2nd edition
    • Gonzalez, Woods: Digital Image Processing
    • Bishop: Pattern Recognition and Machine Learning
  • Exam: written


News

  • May 6rd: exercise sheet is online.
  • May 3rd: Slides of lecture-03 are online.
  • April 24th: There will be no tutorial on Wednesday April 25th. Our first tutorial will be May 9th.
  • April 18th: Slides of lecture-02 are online.
  • April 16th: Slides of lecture-01 are online.
  • April 11th: First lecture takes place on Wednesday 8:15-9:45 in 48-208.
  • April: Lecture starts today!



Slots



Contact

  • Damian Borth
  • Contact email (all requests)
    • Managed by Tushar
    • mdm2018@dfki.de
  • Registration for the class to help us organizing the class
    • please register with an email to mdm2018@dfki.de providing the following information:
      • Name
      • email
      • field of study
      • do want to take the exam?



Schedule

Lecture schedule:

block date lecturer content details slides & demos exercise sheets & materials
1 11.04.18 Damian Borth Introduction course formalities, introduction slides -
2 17.04.18 Damian Borth Multimedia Information Systems definitions, setup, labels, benchmarking slides -
3 24.04.18 (*) no lecture basic decision theory, classification, classifier combination - Ipython/Jupyter Installation link
4 01.05.18 → 02.05.18 Damian Borth 17:15 @ 46-260:: Pattern Recognition (supervised) basic decision theory, classification, classifier combination slides sheet NumPy Website NumPy Tutorial
5 08.05.17 Damian Borth Pattern Recognition (unsupervised) clustering, dimensionality reduction slides -
6 15.05.17 Damian Borth Text Retrieval document retrieval, retrieval models, relevance feedback, data structures slides sheet, URL list
7 22.05.17 Damian Borth Image Representation definitions, features and their properties, invariance, global features, local features - -
8 29.05.17 (*) Similarity Search applications, prototypical architecture, distance measures, object search - -
9 05.06.18 (*) Visual Recognition and Image Classification 1 terminology, applications, face detection, face recognition, object recognition, visual words - -
10 12.06.18 (*) Visual Recognition and Image Classification 2 Bag-of-Words, Support Vector Machine (SVM), Spatial Location Extension, Concept Vocabularies - -
11 19.06.18 (*) Video Analysis shot boundary detection, keyframe extraction, motion estimation & applications, audio analysis - -
12 26.06.18 (*) Deep Learning 1 - DL 101 and Autoencoders end-to-end learning, neural networks, autoencoder - -
13 03.07.18 (*) Deep Learning 2 Convolutional Neural Networks, Long-short Term Memory Networks, Generative Adversarial Networks - -
14 10.07.18 (*) Deep Learning 3 Visual Sentiment Analysis, AdjectiveNounPairs, DeepSentiBank - -



     
Last modified:: 16.05.2018