3 citations · 11 across the 12 of their papers we have counts for
12 papers
Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic Grasping
Anas Gouda, Max Schwarz, Christopher Reining +2
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 develope…
Kontextbasierte Aktivitätserkennung -- Synergie von Mensch und Technik in der Social Networked Industry
Friedrich Niemann, Christopher Reining
In a social networked industry, the focus is on collaboration between humans and technology. Communication is the basic prerequisite for synergetic collaboration between all player…
Object Pose Estimation Annotation Pipeline for Multi-view Monocular Camera Systems in Industrial Settings
Hazem Youssef, Frederik Polachowski, Jérôme Rutinowski +2
Object localization, and more specifically object pose estimation, in large industrial spaces such as warehouses and production facilities, is essential for material flow operation…
Multi-Channel Time-Series Person and Soft-Biometric Identification
Nilah Ravi Nair, Fernando Moya Rueda, Christopher Reining +1
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 ap…
Semi-Automated Computer Vision based Tracking of Multiple Industrial Entities -- A Framework and Dataset Creation Approach
Jérôme Rutinowski, Hazem Youssef, Sven Franke +4
This contribution presents the TOMIE framework (Tracking Of Multiple Industrial Entities), a framework for the continuous tracking of industrial entities (e.g., pallets, crates, ba…
Dataset Bias in Human Activity Recognition
Nilah Ravi Nair, Lena Schmid, Fernando Moya Rueda +3
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 physic…
On the Applicability of Synthetic Data for Re-Identification
Jérôme Rutinowski, Bhargav Vankayalapati, Nils Schwenzfeier +2
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-ident…
A Grid-based Sensor Floor Platform for Robot Localization using Machine Learning
Anas Gouda, Danny Heinrich, Mirco Hünnefeld +3
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…
Applications of human activity recognition in industrial processes -- Synergy of human and technology
Friedrich Niemann, Christopher Reining, Hülya Bas +1
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 commun…
UAVs for Industries and Supply Chain Management
Shrutarv Awasthi, Nils Gramse, Christopher Reining +1
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…
DoPose-6D dataset for object segmentation and 6D pose estimation
Anas Gouda, Abraham Ghanem, Christopher Reining
Scene understanding is essential in determining how intelligent robotic grasping and manipulation could get. It is a problem that can be approached using different techniques: seen…
pRSL: Interpretable Multi-label Stacking by Learning Probabilistic Rules
Michael Kirchhof, Lena Schmid, Christopher Reining +2
A key task in multi-label classification is modeling the structure between the involved classes. Modeling this structure by probabilistic and interpretable means enables applicatio…