Year: 2020

Application of Reinforcement Learning to a Mining System

Posted on By aline No Comments on Application of Reinforcement Learning to a Mining System
publication

Coming soon: SAMI 2021, January 21-23, 2021http://conf.uni-obuda.hu/sami2021/final.html Paper is out! https://ieeexplore.ieee.org/document/9378663 Abstract Automation techniques have been widely applied in different industry segments, among others, to increase both productivity and safety. In the mining industry, with the usage of such systems, the operator can be removed from hazardous environments without compromising task execution and it is … Read More “Application of Reinforcement Learning to a Mining System” »

Improving the performance of EEG decoding using anchored-STFT in conjunction with gradient norm adversarial augmentation

Posted on By Muhammad Saif-Ur-Rehman No Comments on Improving the performance of EEG decoding using anchored-STFT in conjunction with gradient norm adversarial augmentation
publication, scientific publication

Preprint https://arxiv.org/abs/2011.14694 AbstractObjective. Brain-computer interfaces (BCIs) enable direct communication between humans and machines by translating brain activity into control commands. Electroencephalography (EEG) is one of the most common sources of neural signals because of its inexpensive and non-invasivenature. However, interpretation of EEG signals is non-trivial because EEG signals have a low spatial resolution and are … Read More “Improving the performance of EEG decoding using anchored-STFT in conjunction with gradient norm adversarial augmentation” »

SpikeDeep-Classifier: A deep-learning based fully automatic offline spike sorting algorithm

Posted on By Muhammad Saif-Ur-Rehman No Comments on SpikeDeep-Classifier: A deep-learning based fully automatic offline spike sorting algorithm
publication

Publication in Journal of Neural Engineering https://doi.org/10.1088/1741-2552/abc8d4 Abstract Objective. Advancements in electrode design have resulted in micro-electrode arrays with hundreds of channels for single cell recordings. In the resulting electrophysiological recordings, each implanted electrode can record spike activity (SA) of one or more neurons along with background activity (BA). The aim of this study is … Read More “SpikeDeep-Classifier: A deep-learning based fully automatic offline spike sorting algorithm” »

An investigation of existence of the adversarial inputs in the brain-computer interface (BCI) applications (Thesis proposal)

Posted on By Muhammad Saif-Ur-Rehman No Comments on An investigation of existence of the adversarial inputs in the brain-computer interface (BCI) applications (Thesis proposal)
teaching

Masterarbeitsthema Abstract: Brain-computer interface (BCI), “the recipe of decoding intended actions from neural signals” is a way forward towards creating an intelligent neuroprosthetics solution. Deep learning (DL) algorithms provide many state-of-the-art results in the rapidly growing BCI applications. Despite this fact, DL algorithms are fragile against synthetic inputs called “adversarial inputs”. These inputs can be … Read More “An investigation of existence of the adversarial inputs in the brain-computer interface (BCI) applications (Thesis proposal)” »

Online SpikeDeep-Classifier: The supervised learning based online spike sorting algorithm (Thesis-Proposal)

Posted on By Muhammad Saif-Ur-Rehman No Comments on Online SpikeDeep-Classifier: The supervised learning based online spike sorting algorithm (Thesis-Proposal)
teaching

Abstract: A spike sorting algorithm allows the identification of the activity of each neural source. We published two studies SpikeDeeptector and SpikeDeep-Classifier in the journal of the neural engineering. This study is based on our previously published studies. In this study, we aim to identify the neural activity of each source, online. More importantly, we … Read More “Online SpikeDeep-Classifier: The supervised learning based online spike sorting algorithm (Thesis-Proposal)” »

Autonomous Systems: MyoBoy: Game control via gesture recognition using the Myo wristband

Posted on By jannis 1 Comment on Autonomous Systems: MyoBoy: Game control via gesture recognition using the Myo wristband
teaching

Student project within the module “Autonomous Systems” at Ruhr West University of Applied Sciences. Students Nils Biernacki, Lukas Kandora, Katharina Stefanski, Philipp Student Supervision M.Sc. Nique Schmidt and Prof. Dr. Ioannis Iossifidis Project site https://gitlab.hs-ruhrwest.de/iSystemsStudentProjects/2020/eeg-emg-gamecontroller live demo

Autonomous Systems: dialogBot for simulated conversation

Posted on By jannis No Comments on Autonomous Systems: dialogBot for simulated conversation
teaching

Student project within the module “Autonomous Systems” at Ruhr West University of Applied Sciences. Students Lars Buck, Tim Habermann Supervision M.Sc. Stephan Lehmler, Prof. Dr. Ioannis Iossifidis Project site The project aim to create a dialog bot with an animated avatar able to have a casual conversation and to assist the user. The dialog bot is supposed … Read More “Autonomous Systems: dialogBot for simulated conversation” »

Autonomous Systems: Generic Gesture Recognition and Classification for Game Control

Posted on By jannis No Comments on Autonomous Systems: Generic Gesture Recognition and Classification for Game Control
teaching

Student project within the module “Autonomous Systems” at Ruhr West University of Applied Sciences. Students Merih Türkoglu, Matthias Weibrecht Supervision Prof. Dr. Ioannis Iossifidis Project site https://gitlab.hs-ruhrwest.de/iSystemsStudentProjects/2020/generic-gesture-recognition-and-classification-for-game-vr-control The goal of this project is to develop a gesture recognition based on common webcams and low budget hardware to implement hand gesture control in any application. live demo

Autonomous Systems: ML Based Stock Market Prediction

Posted on By jannis No Comments on Autonomous Systems: ML Based Stock Market Prediction
teaching

Student project within the module “Autonomous Systems” at Ruhr West University of Applied Sciences. Students Alexander Klee, Mahdi El Mesoudy,Jan Dehlen Supervision M.Sc. Felix Grün and M.Sc. Stephan Lehmer Prozent site https://gitlab.hs-ruhrwest.de/iSystemsStudentProjects/2020/ml-based-stockmarket-prediction live demo of the command line tool