What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Artificial intelligence
Scalable Video Coding, Computer network, Real-time computing, Multiview Video Coding and Codec are his primary areas of study.
Thomas Schierl has included themes like Video quality, Server and Smacker video in his Scalable Video Coding study.
His Computer network research is multidisciplinary, incorporating elements of Forward error correction and Popularity.
His study in Real-time computing is interdisciplinary in nature, drawing from both Entropy encoding, Decoding methods, Binary number, Video bitstream and Byte.
His studies in Multiview Video Coding integrate themes in fields like Coding tree unit, Video processing and Parallel computing.
Thomas Schierl has researched Digital Video Broadcasting in several fields, including Digital multimedia broadcasting and Bitstream.
His most cited work include:
- Mobile Video Transmission Using Scalable Video Coding (295 citations)
- Parallel Scalability and Efficiency of HEVC Parallelization Approaches (197 citations)
- iDASH: improved dynamic adaptive streaming over HTTP using scalable video coding (105 citations)
What are the main themes of his work throughout his whole career to date?
Thomas Schierl focuses on Computer network, Real-time computing, Scalable Video Coding, Decoding methods and Network packet.
His Computer network research includes elements of Forward error correction and Distributed computing.
The Real-time computing study combines topics in areas such as Viewport, Computer hardware, Encoding, Reduction and Rendering.
His research integrates issues of Multiview Video Coding, Quality of service, Codec, Digital Video Broadcasting and Video quality in his study of Scalable Video Coding.
His research in Multiview Video Coding focuses on subjects like Coding tree unit, which are connected to Context-adaptive binary arithmetic coding.
His Decoding methods research incorporates themes from Parallel computing, Artificial intelligence and Hybrid automatic repeat request.
He most often published in these fields:
- Computer network (32.70%)
- Real-time computing (27.96%)
- Scalable Video Coding (26.54%)
What were the highlights of his more recent work (between 2018-2021)?
- Real-time computing (27.96%)
- Rendering (4.74%)
- Network packet (14.22%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Real-time computing, Rendering, Network packet, Video streaming and Algorithm.
His Real-time computing research integrates issues from Viewport, Latency, Reduction and Baseline system.
His Network packet study is focused on Computer network in general.
Thomas Schierl integrates Computer network and Dash in his studies.
His study looks at the relationship between Video streaming and fields such as Multimedia, as well as how they intersect with chemical problems.
His study in the fields of Entropy encoding under the domain of Algorithm overlaps with other disciplines such as Extension.
Between 2018 and 2021, his most popular works were:
- Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G (18 citations)
- Delay Impact on MPEG OMAF’s Tile-Based Viewport-Dependent 360° Video Streaming (16 citations)
- Low-latency cloud-based volumetric video streaming using head motion prediction (5 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Artificial intelligence
His primary scientific interests are in Rendering, Artificial intelligence, Real-time computing, Augmented reality and Mobile device.
His research in Rendering intersects with topics in Multimedia, Metadata, Virtual reality and JavaScript.
Thomas Schierl interconnects Block error, Decoding methods, Computer vision and Hybrid automatic repeat request in the investigation of issues within Artificial intelligence.
His studies in Computer vision integrate themes in fields like Data stream mining and Section.
He performs integrative study on Real-time computing and Edge server.
His Augmented reality research is multidisciplinary, incorporating perspectives in Latency, Representation and Latency.
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