http://dl.gi.de/handle/20.500.12116/37770 2026-07-22T20:35:22Z http://dl.gi.de/handle/20.500.12116/37784 Bicycle Detection from Top View Perspective in Surveillance System using Convolutional Neural Network Ramkumar, Sanal Darshid Gesellschaft für Informatik Bicycle detection and tracking from top view perspective using deep learning is a highly active research area for video surveillance and automatic ticket generation in Advanced Public Transportation System (APTS). People detection using conventional cameras has received massive attention for video surveillance inside public transportation systems but inattentive towards bicycle detection. Experimentation is performed on You Only Look Once (YOLO), Faster Regional-Convolutional Neural Network (Faster R-CNN) and Single Shot Multibox Detector (SSD). Due to the sparse availability of dataset for this work, a customized dataset was recorded in the Media Computing lab, Junior Professorship of Media Computing, TU Chemnitz, Germany. The customized dataset was recorded using a wide-angle smart stereo sensor (S2000, Intenta GmbH) mounted in bird’s eye perspective. Furthermore, two additional datasets were recorded using a mobile camera representing indoor and outdoor bicycle parking area. This paper provides best case solution for bicycle detection from a top view perspective. 2021-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/37786 Anomaly Detection in Motion Timeseries using the Bosch XDK and Dynamic Time Warping Mejía, Julián Rico; Isaías, Oscar Aguilar Aguila; Paschapur, Priyanka Gesellschaft für Informatik This paper presents the development of an anomaly detector for robotic movements using the dynamic time warping (DTW) algorithm and its implementation in Matlab. Data was collected by mounting the Bosch Cross-Domain Development Kit (XDK) sensor on a collaborative robot arm (Cobot), aiming at industrial applications in need for motion anomaly detection during repetitive tasks. The paper discusses practical issues like parameter tuning as well as algorithmic variants such as de­coupling accelerometer and gyroscope data. 2021-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/37785 Multiple Sequence Alignment using Deep Reinforcement Learning Joeres, Roman Gesellschaft für Informatik Multiple sequence alignment (MSA) is one of the primal problems in biology and bioinformatics. The question of how to align multiple sequences correctly is crucial for many other fields of research, e.g., gaining information about the evolutionary distance of two or more sequences and therefore about their corresponding species, finding protein targets for drugs, or finding a drug for a certain target protein. Reinforcement learning (RL), and especially deep reinforcement learning (DRL), has become popular in recent years. To name just a few, DRL has shown major success in complex games such as Atari Games, Chess, and Go. We model the problem of aligning multiple sequences as a Markov decision process (MDP) and examine the performance of different (D)RL algorithms compared to state-of-the-art tools. 2021-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/37782 Künstliche Intelligenz im Requirements Engineering Breuninger, Judith; Kücher, Franziska; Misic, Natali Gesellschaft für Informatik Dem Einsatz von Künstlicher Intelligenz (KI) im Requirements Engineering (RE) wird ein hohes Potenzial zugeschrieben. Der Stand der Forschung gestaltet sich jedoch unübersichtlich. Im Rahmen einer Systematischen Literaturrecherche werden 27 wissenschaftliche Publikationen aus drei Datenbanken identifiziert und analysiert. Anschließend werden diese in die RE-Phasen der Anforderungserhebung, -analyse, -spezifikation und -validierung eingeordnet und zusammengefasst. Die Ergebnisse zeigen, dass KI in den vier Phasen eingesetzt wird, allerdings ist die Anwendung unterschiedlich stark ausgeprägt. Weitere tiefgehende Forschungsarbeit, insbesondere zum Einsatz von KI in der Anforderungsvalidierung, ist notwendig. Die vorliegende Arbeit stellt dafür einen wesentlichen Ausgangspunkt dar, indem sie einen strukturierten Überblick der verschiedenen KI-Methoden zum Einsatz im RE aufzeigt und diskutiert. 2021-01-01T00:00:00Z