Manh Nguyen-Duc

Manh Nguyen-Duc
Technische Universität Berlin | TUB

Bachelor of Applied Science

About

8
Publications
1,187
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
17
Citations

Publications

Publications (8)
Preprint
Full-text available
We present CQELS 2.0, the second version of Continuous Query Evaluation over Linked Streams. CQELS 2.0 is a platform-agnostic federated execution framework towards semantic stream fusion. In this version, we introduce a novel neural-symbolic stream reasoning component that enables specifying deep neural network (DNN) based data fusion pipelines via...
Preprint
Full-text available
Stream processing and reasoning is getting considerable attention in various application domains such as IoT, Industry IoT and Smart Cities. In parallel, reasoning and knowledge-based features have attracted research into many areas of robotics, such as robotic mapping, perception and interaction. To this end, the Semantic Stream Reasoning (SSR) fr...
Preprint
Full-text available
It is commonly acknowledged that the availability of the huge amount of (training) data is one of the most important factors for many recent advances in Artificial Intelligence (AI). However, datasets are often designed for specific tasks in narrow AI sub areas and there is no unified way to manage and access them. This not only creates unnecessary...
Poster
Full-text available
Computer Vision (CV) has recently achieved significant improvements , thanks to the evolution of deep learning. Along with advanced architectures and optimisations of deep neural networks, CV data for (cross-datasets) training, validating, and testing contributes greatly to the performance of CV models. Many CV datasets have been created for differ...
Conference Paper
Full-text available
Video streams are becoming ubiquitous in smart cities and traffic monitoring. Recent advances in computer vision with deep neural networks enable querying a rich set of visual features from these video streams. However, it is challenging to deploy these queries on edge devices due to the resource intensive nature of the computing operations of this...
Chapter
Full-text available
The wide adoption of increasingly cheap and computationally powerful single-board computers, has triggered the emergence of new paradigms for collaborative data processing among IoT devices. Motivated by the billions of ARM chips having been shipped as IoT gateways so far, our paper proposes a novel continuous federation approach that uses RDF Stre...
Conference Paper
Full-text available
This paper presents a solution to the Grand Challenge using CQELS (Continuous Query Evaluation over Linked Stream), a general execution framework to build RDF Stream Processing engines to answer continuous analytical queries. It provides an efficient execution architecture whereby incremental computing algorithms can be implemented to boost the per...