Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Reining, Christopher"'
Foundation models are a strong trend in deep learning and computer vision. These models serve as a base for applications as they require minor or no further fine-tuning by developers to integrate into their applications. Foundation models for zero-sh
Externí odkaz:
http://arxiv.org/abs/2404.06277
In a social networked industry, the focus is on collaboration between humans and technology. Communication is the basic prerequisite for synergetic collaboration between all players. It includes non-verbal as well as verbal interactions. To enable no
Externí odkaz:
http://arxiv.org/abs/2402.05480
Autor:
Youssef, Hazem, Polachowski, Frederik, Rutinowski, Jérôme, Roidl, Moritz, Reining, Christopher
Object localization, and more specifically object pose estimation, in large industrial spaces such as warehouses and production facilities, is essential for material flow operations. Traditional approaches rely on artificial artifacts installed in th
Externí odkaz:
http://arxiv.org/abs/2310.14914
Multi-channel time-series datasets are popular in the context of human activity recognition (HAR). On-body device (OBD) recordings of human movements are often preferred for HAR applications not only for their reliability but as an approach for ident
Externí odkaz:
http://arxiv.org/abs/2304.01585
Autor:
Rutinowski, Jérôme, Youssef, Hazem, Franke, Sven, Priyanta, Irfan Fachrudin, Polachowski, Frederik, Roidl, Moritz, Reining, Christopher
This contribution presents the TOMIE framework (Tracking Of Multiple Industrial Entities), a framework for the continuous tracking of industrial entities (e.g., pallets, crates, barrels) over a network of, in this example, six RGB cameras. This frame
Externí odkaz:
http://arxiv.org/abs/2304.00950
Autor:
Nair, Nilah Ravi, Schmid, Lena, Rueda, Fernando Moya, Pauly, Markus, Fink, Gernot A., Reining, Christopher
When creating multi-channel time-series datasets for Human Activity Recognition (HAR), researchers are faced with the issue of subject selection criteria. It is unknown what physical characteristics and/or soft-biometrics, such as age, height, and we
Externí odkaz:
http://arxiv.org/abs/2301.10161
Autor:
Rutinowski, Jérôme, Vankayalapati, Bhargav, Schwenzfeier, Nils, Acosta, Maribel, Reining, Christopher
This contribution demonstrates the feasibility of applying Generative Adversarial Networks (GANs) on images of EPAL pallet blocks for dataset enhancement in the context of re-identification. For many industrial applications of re-identification metho
Externí odkaz:
http://arxiv.org/abs/2212.10105
Autor:
Gouda, Anas, Heinrich, Danny, Hünnefeld, Mirco, Priyanta, Irfan Fachrudin, Reining, Christopher, Roidl, Moritz
Wireless Sensor Network (WSN) applications reshape the trend of warehouse monitoring systems allowing them to track and locate massive numbers of logistic entities in real-time. To support the tasks, classic Radio Frequency (RF)-based localization ap
Externí odkaz:
http://arxiv.org/abs/2212.04721
This work aims at showing that it is feasible and safe to use a swarm of Unmanned Aerial Vehicles (UAVs) indoors alongside humans. UAVs are increasingly being integrated under the Industry 4.0 framework. UAV swarms are primarily deployed outdoors in
Externí odkaz:
http://arxiv.org/abs/2212.03346
Human-technology collaboration relies on verbal and non-verbal communication. Machines must be able to detect and understand the movements of humans to facilitate non-verbal communication. In this article, we introduce ongoing research on human activ
Externí odkaz:
http://arxiv.org/abs/2212.02266