ADR Awareness Centre

This lecture overviews Discrete Fourier Transform that has many applications in digital signal processing and analysis and in power spectrum estimation.

This lecture overviews Blockchain technology that has many applications in cryptocurrencies, e-commerce and identity management.

This lecture is held every winter semester as part of the Audio Signal Processing & Audio Systems Module at TU Ilmenau.

This lecture overviews Athlete Motion Analysis that has many applications in Human-centered Computing, Image and Video Analysis and Sports coaching. It covers the following topics in detail: Motion Caption. Body pose. Rigid object motion.

This lecture overviews Gesture Recognition that has many applications in Human-Machine Interaction (HMI), Human-Robot Interaction (HRI), Sign Language, Navigation or/and the manipulation in VR environment and Distance learning.

This lecture overviews that has many applications in Human-centered Computing, Image and Video Analysis, Surveillance and Social Media Analytics. It covers the following topics in detail: Face recognition/identification. Face verification.

This lecture overviews  object pose estimation   that has many applications in Human-Robotic Interaction (HRI), Robotics and Augmented Reality.

This lecture overviews Orthogonal Signal Transforms. Fourier Series that has many applications in signal processing, analysis and compression.

AI is a rapidly emerging field that has opened up new vistas of innovation and creativity. From intelligent systems to self-driving cars, AI has transformed the way we live and work.

This lecture overviews Hidden Markov Models that have many applications in Data Analytics and Signal Analysis. It covers the following topics in detail: Markov Chains. Hidden Markov Chains: Viterbi algorithm, Forward-backward algorithm.

This lecture overviews Face Clustering that has many applications in Human-centered Computing, Image and Video Analysis and Social Media Analytics. It covers the following topics in detail: Facial image similarities. Similarity graphs.

This lecture overviews Graph Signal Processing that has many applications in Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Linear 1D convolution. Cyclic 1D convolution. Graph Basics.