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Carsten Griwodz
Researcher at University of Oslo
Publications - 238
Citations - 5263
Carsten Griwodz is an academic researcher from University of Oslo. The author has contributed to research in topics: The Internet & Video quality. The author has an hindex of 32, co-authored 230 publications receiving 4366 citations. Previous affiliations of Carsten Griwodz include Simula Research Laboratory & IBM.
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Proceedings ArticleDOI
Using multiple links to increase the performance of bandwidth-intensive UDP-based applications
TL;DR: A transparent solution for proxy-based bandwidth aggregation that is able to overcome the different deployment and link heterogeneity challenges present in real-world networks, in terms of support for middle-boxes, congestion control, a client-based resequencer and support for all operating systems is presented.
Proceedings ArticleDOI
TCP mechanisms for improving the user experience for time-dependent thin-stream applications
TL;DR: The experimental results show that modifications to the TCP retransmission mechanisms in the Linux kernel allow TCP to recover earlier from packet loss, and user surveys indicate that the majority of users easily detect improvements in the perceived quality of the tested applications.
Journal ArticleDOI
Efficient Live and on-Demand Tiled HEVC 360 VR Video Streaming
Carsten Griwodz,Mattis Jeppsson,Håvard Espeland,Tomas Kupka,Ragnar Langseth,Andreas Petlund,Peng Qiaoqiao,Chuansong Xue,Konstantin Pogorelov,Micheal Alexander Riegler,Dag Johansen,Pål Halvorsen +11 more
TL;DR: Huang et al. as discussed by the authors presented a live streaming system which strikes a trade-off between bandwidth usage and the video quality in the user's field-of-view, and demonstrated the performance and illustrate the trade-offs through real-world experiments where they can report comparable bandwidth savings to existing on-demand approaches.
Journal ArticleDOI
Layer-encoded video streaming a proxy's perspective
TL;DR: A proxy's perspective in an architecture that supports efficient distribution of recorded video data in today's Internet and solutions to improve the performance are discussed, mainly from the perspective of a proxy cache.
A Comparison of Deep Learning with Global Features for Gastrointestinal Disease Detection.
Konstantin Pogorelov,Michael Riegler,Pål Halvorsen,Carsten Griwodz,Thomas de Lange,Kristin Ranheim Randel,Sigrun Losada Eskeland,Duc-Tien Dang-Nguyen,Olga Ostroukhova,Mathias Lux,Concetto Spampinato +10 more
TL;DR: A system based on global features and deep neural networks is proposed for the 2017 Multimedia for Medicine Medico Task of the MediaEval 2017 Benchmark and preliminary results comparing the approaches are presented.