SLOT1: AI-Bot playing Doom - Applied Deep Reinforcement Learning - Rodolphe Masson
In this presentation, Rodolphe shows the results (videos) of his investigations of various deep reinforcement learning techniques, standard deep Q-network (DQN), Replay Memory (RM), Double DQN and Dueling DQN, applied to a software agent whose goal is to play autonomously the game Doom through three different scenarios of increasing complexity, “basic”, “health gathering supreme” and “deadly corridor”, from the ViZDoomEnvironment.
Then he concludes on the most promising techniques to pursue this project in the future like Asynchronous Advantage Actor-Critic (A3C) and Direct Future Predictions (DFP)
SLOT2: ColorTransfer: Bringing New Life to Old Photos Using Neural Nets - Preslav Rachev
Convolutional neural networks are all the rage nowadays, especially, when it comes to digital imagery. They are equally well suited for image classification, as well as for generating new images, based on certain pre-trained models. Can they then help bring a colourful life back to old black and white photos? Let’s check it out!
Inspired by existing research on photo colorization, I have devised my own set of empirical experiments based around the use of CNNs and autoencoders.
SLOT3: Advanced Analytics and IoT explained with a show case - Florian Haeussinger
The project implements an IoT-Showcase with small toy cars of the brand Anki OVERDRIVE. The vehicles have an IR-Sensor, a microprocessor and an electro motor. Data and commands are transmitted to the vehicles or the controller using Bluetooth Low Energy (BLE).
The collected data is stored in a Lambda-Architecture, which is based on open source software solutions. From there, various scenarios like anti-collision or product-improvement using IoT technologies and machine learning methods were developed.
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