@misc {42763,
	title = {7 Things They Don{\textquoteright}t Tell You About Streaming Analytics},
	howpublished = {Demuxed},
	year = {2022},
	url = {https://2022.demuxed.com/$\#$speakers},
	author = {Midoglu, Cise}
}
@misc {42446,
	title = {ACM Multimedia Grand Challenge on Detecting Cheapfakes},
	year = {2022},
	note = {https://2022.acmmm.org/call-for-grand-challenge-submissions/},
	publisher = {ACM},
	address = {ACM Multimedia Conference (MM)},
	url = {https://detecting-cheapfakes.github.io},
	author = {Aneja, Shivangi and Midoglu, Cise and Dang-Nguyen, Duc-Tien and Khan, Sohail and Riegler, Michael and Halvorsen, P{\r a}l and Bregler, Chris and Adsumilli, Balu}
}
@misc {42445,
	title = {AI-Based Video Production for Soccer},
	howpublished = {FOKUS Media Web Symposium},
	year = {2022},
	url = {https://www.fokus.fraunhofer.de/go/mws},
	author = {Midoglu, Cise}
}
@inproceedings {gautam2022assisting,
	title = {Assisting Soccer Game Summarization via Audio Intensity Analysis of Game Highlights},
	journal = {Proceedings of 12th IOE Graduate Conference},
	volume = {12},
	year = {2022},
	month = {October},
	pages = {25 {\textendash} 32},
	publisher = {Institute of Engineering, Tribhuvan University, Nepal},
	abstract = {In association football, the development of multimodal summaries is of great importance to both broadcasters and spectators since a large number of viewers choose to follow just the soccer game highlights. The fundamental drive for the development of summarization systems is the requirement to manage huge amounts of data in different formats. By highlighting the most pertinent facts and limiting or omitting unnecessary aspects, summarization helps avoid "information overload." The properties of the audio signals during a particular event can be used to calculate excitement around that event and filter events based on their importance. A root-mean-square (RMS) analysis of audio events was carried out to analyse the excitement across the events in the SoccerNet dataset. It was clearly seen that important events with excitement have a high and distinguishable RMS audio intensity. It was also observed that the generated noise of the crowd was significantly different across various events and if it happened for the home or away team. The intensity was higher for events related to the home team. Likewise, as the wavelet has the benefit of integrating a wave with a specific period, Morlet wavelet analysis was performed for various event types, and the power of the signal across various wavelet scales was analyzed. A distinct signature across various wavelet scales was observed for different events.},
	keywords = {association football, audio signal, soccer game highlights, summarization},
	doi = {http://dx.doi.org/10.13140/RG.2.2.34457.70240/1},
	url = {http://conference.ioe.edu.np/publications/ioegc12/IOEGC-12-004-12009.pdf},
	author = {Gautam, Sushant and Midoglu, Cise and Saeed Shafiee {Sabet} and Dinesh Baniya {Kshatri} and Halvorsen, P{\r a}l}
}
@misc {42443,
	title = {Automatic Thumbnail Selection for Soccer using Machine Learning},
	year = {2022},
	address = {NORA Annual Conference, Stavanger, Norway},
	author = {Husa, Andreas and Midoglu, Cise and Halvorsen, P{\r a}l}
}
@inproceedings {42447,
	title = {Automatic Thumbnail Selection for Soccer Videos using Machine Learning},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSys {\textquoteright}22)},
	year = {2022},
	pages = {73-85},
	publisher = {ACM},
	doi = {10.1145/3524273.3528182},
	author = {Husa, Andreas and Midoglu, Cise and Hammou, Malek and Hicks, Steven and Johansen, Dag and Kupka, Tomas and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {42709,
	title = {Comparison of Crowdsourced and Remote Subjective User Studies: A Case Study of Investigative Child Interviews},
	journal = {The 14th International Conference on Quality of Multimedia Experience},
	year = {2022},
	publisher = {IEEE},
	doi = {10.1109/QoMEX55416.2022.9900900},
	url = {https://ieeexplore.ieee.org/document/9900900},
	author = {Saeed Shafiee {Sabet} and Midoglu, Cise and Syed Zohaib {Hassan} and Salehi, Pegah and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@phdthesis {43131,
	title = {Empirical Analysis of QoS and QoE in Mobile Broadband Networks},
	volume = {PhD},
	year = {2022},
	author = {Midoglu, Cise}
}
@inproceedings {43138,
	title = {Experiences and Lessons Learned from a Crowdsourced-Remote Hybrid User Survey Framework},
	journal = {2022 IEEE International Symposium on Multimedia (ISM)},
	year = {2022},
	pages = {161-162},
	publisher = {IEEE},
	address = {Italy},
	abstract = {Subjective user studies are important to ensure the fidelity and usability of systems that generate multimedia content. Testing how end-users and domain experts perceive multimedia assets might provide crucial information. In this paper, we present our experiences with the open source hybrid crowdsourced-remote user survey framework called Huldra, which is intended for conducting web-based subjective user studies and aims to integrate the individual benefits associated with traditional, crowdsourced, and remote methods. We disseminate our experiences and insights from two actively deployed use cases and discuss challenges and opportunities associated with using Huldra as a framework for conducting user studies.},
	doi = {10.1109/ISM55400.2022.00035},
	url = {https://ieeexplore.ieee.org/document/10019678},
	author = {Midoglu, Cise and Stor{\r a}s, Andrea and Saeed Shafiee {Sabet} and Hammou, Malek and Hicks, Steven and Str{\"u}mke, Inga and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@article {42761,
	title = {Exploration of Different Time Series Models for Soccer Athlete Performance Prediction},
	journal = {MDPI Engineering Proceedings},
	volume = {18},
	year = {2022},
	pages = {37},
	publisher = {MDPI},
	doi = {10.3390/engproc2022018037},
	author = {Kulakou, Siarhei and Ragab, Nourhan and Midoglu, Cise and Boeker, Matthias and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {42441,
	title = {HOST-ATS: Automatic Thumbnail Selection with Dashboard-Controlled ML Pipeline and Dynamic User Survey},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSys {\textquoteright}22)},
	year = {2022},
	pages = {334-340},
	publisher = {ACM},
	doi = {10.1145/3524273.3532908},
	author = {Husa, Andreas and Midoglu, Cise and Hammou, Malek and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {42442,
	title = {Huldra: A Framework for Collecting Crowdsourced Feedback on Multimedia Assets},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSys {\textquoteright}22)},
	year = {2022},
	pages = {203-209},
	publisher = {ACM},
	doi = {10.1145/3524273.3532887},
	author = {Hammou, Malek and Midoglu, Cise and Hicks, Steven and Stor{\r a}s, Andrea and Saeed Shafiee {Sabet} and Str{\"u}mke, Inga and Riegler, Michael and Halvorsen, P{\r a}l}
}
@misc {28442,
	title = {MMSys{\textquoteright}22 Grand Challenge on AI-based Video Production for Soccer},
	year = {2022},
	publisher = {arXiv},
	url = {https://arxiv.org/abs/2202.01031},
	author = {Midoglu, Cise and Hicks, Steven and Thambawita, Vajira and Kupka, Tomas and Halvorsen, P{\r a}l}
}
@inproceedings {28322,
	title = {Multimedia streaming analytics: quo vadis?},
	journal = {MHV {\textquoteright}22: Mile-High Video Conference},
	year = {2022},
	pages = {62 - 69},
	publisher = {ACM},
	address = {Denver, Colorado, USA},
	isbn = {9781450392228},
	doi = {10.1145/3510450.3517321},
	url = {https://dl.acm.org/doi/10.1145/3510450.3517321},
	author = {Midoglu, Cise and Avelino, Mariana and Shri Hari {Gopalakrishnan} and Pham, Stefan and Halvorsen, P{\r a}l}
}
@inbook {42537,
	title = {Smittestopp Backend},
	booktitle = { Smittestopp - A Case Study on Digital Contact Tracing},
	volume = {11},
	year = {2022},
	month = {06/2022},
	pages = {29 - 62},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {An efficient backend solution is of great importance for any large-scale system, and Smittestopp is no exception. The Smittestopp backend comprises various components for user and device registration, mobile app data ingestion, database and cloud operations, and web interface support. This chapter describes our journey from a vague idea to a deployed system. We provide an overview of the system internals and design iterations and discuss the challenges that we faced during the development process, along with the lessons learned. The Smittestopp backend handled around 1.5 million registered devices and provided various insights and analyses before being discontinued a few months after its launch.},
	isbn = {978-3-031-05465-5},
	issn = {2512-1677},
	doi = {10.1007/978-3-031-05466-2_3},
	url = {https://link.springer.com/content/pdf/10.1007/978-3-031-05466-2.pdf},
	author = {Midoglu, Cise and Ragan-Kelley, Benjamin and Reinemo, Sven-Arne and Jahren, Jon and Halvorsen, P{\r a}l},
	editor = {Elmokashfi, Ahmed and Lysne, Olav and Naumova, Valeriya}
}
@misc {42444,
	title = {Soccer Athlete Performance Prediction using Time Series Analysis},
	howpublished = {NORA Annual Conference},
	year = {2022},
	author = {Ragab, Nourhan and Midoglu, Cise and Halvorsen, P{\r a}l}
}
@inproceedings {42762,
	title = {Soccer Game Summarization using Audio Commentary, Metadata, and Captions},
	journal = {NarSUM {\textquoteright}22: Proceedings of the 1st Workshop on User-centric Narrative Summarization of Long Videos},
	year = {2022},
	pages = {13-22},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450394932},
	doi = {10.1145/3552463.3557019},
	url = {https://doi.org/10.1145/3552463.3557019},
	author = {Gautam, Sushant and Midoglu, Cise and Saeed Shafiee {Sabet} and Dinesh Baniya {Kshatri} and Halvorsen, P{\r a}l}
}
@misc {42764,
	title = {Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations},
	year = {2022},
	publisher = {arXiv},
	doi = {10.48550/arXiv.2204.00617},
	url = {https://arxiv.org/abs/2204.00617},
	author = {Hicks, Steven and Stor{\r a}s, Andrea and Riegler, Michael and Midoglu, Cise and Hammou, Malek and de Lange, Thomas and Parasa, Sravanthi and Halvorsen, P{\r a}l and Str{\"u}mke, Inga}
}
@article {28313,
	title = {AI-Based Video Clipping of Soccer Events},
	journal = {Machine Learning and Knowledge Extraction},
	volume = {3},
	year = {2021},
	month = {12/2021},
	pages = {990 - 1008},
	publisher = {MDPI},
	abstract = {The current gold standard for extracting highlight clips from soccer games is the use of manual annotations and clippings, where human operators define the start and end of an event and trim away the unwanted scenes. This is a tedious, time-consuming, and expensive task, to the extent of being rendered infeasible for use in lower league games. In this paper, we aim to automate the process of highlight generation using logo transition detection, scene boundary detection, and optional scene removal. We experiment with various approaches, using different neural network architectures on different datasets, and present two models that automatically find the appropriate time interval for extracting goal events. These models are evaluated both quantitatively and qualitatively, and the results show that we can detect logo and scene transitions with high accuracy and generate highlight clips that are highly acceptable for viewers. We conclude that there is considerable potential in automating the overall soccer video clipping process.\&nbsp;\&nbsp;},
	doi = {10.3390/make3040049},
	url = {https://www.mdpi.com/2504-4990/3/4/49/pdf},
	author = {Joakim Olav {Valand} and Kadragic, Haris and Hicks, Steven and Thambawita, Vajira and Midoglu, Cise and Kupka, Tomas and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {28315,
	title = {Automated Clipping of Soccer Events using Machine Learning},
	journal = {IEEE International Symphosium of Multimedia (ISM)},
	year = {2021},
	month = {12/2021},
	publisher = { IEEE},
	doi = {10.1109/ISM52913.2021.00042},
	author = {Valand, Joakim and Kadragic, Haris and Hicks, Steven and Thambawita, Vajira and Midoglu, Cise and Kupka, Tomas and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {28314,
	title = {Automated Event Detection and Classification in Soccer: The Potential of Using Multiple Modalities},
	journal = {Machine Learning and Knowledge Extraction},
	volume = {3},
	year = {2021},
	month = {12/2021},
	pages = {1030 - 1054},
	publisher = {MDPI},
	abstract = {Detecting events in videos is a complex task, and many different approaches, aimed at a large variety of use-cases, have been proposed in the literature. Most approaches, however, are unimodal and only consider the visual information in the videos. This paper presents and evaluates different approaches based on neural networks where we combine visual features with audio features to detect (spot) and classify events in soccer videos. We employ model fusion to combine different modalities such as video and audio, and test these combinations against different state-of-the-art models on the SoccerNet dataset. The results show that a multimodal approach is beneficial. We also analyze how the tolerance for delays in classification and spotting time, and the tolerance for prediction accuracy, influence the results. Our experiments show that using multiple modalities improves event detection performance for certain types of events.},
	doi = {10.3390/make3040051},
	url = {https://www.mdpi.com/2504-4990/3/4/51/pdf},
	author = {Olav Andre Nerg {Rongved} and Stige, Markus and Hicks, Steven and Thambawita, Vajira and Midoglu, Cise and Zouganeli, Evi and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {27701,
	title = {Large scale {\textquotedblleft}speedtest{\textquotedblright} experimentation in Mobile Broadband Networks},
	journal = {Computer Networks},
	volume = {184},
	year = {2021},
	month = {Oct-17-2021},
	pages = {107629},
	publisher = {Elsevier},
	issn = {13891286},
	doi = {10.1016/j.comnet.2020.107629},
	author = {Midoglu, Cise and Kousias, Konstantinos and Alay, {\"O}zg{\"u} and Lutu, Andra and Argyriou, Antonios and Riegler, Michael and Griwodz, Carsten}
}
@misc {aneja2021mmsys21,
	title = {MMSys{\textquoteright}21 Grand Challenge on Detecting Cheapfakes},
	year = {2021},
	publisher = {arXiv},
	author = {Aneja, Shivangi and Midoglu, Cise and Dang-Nguyen, Duc-Tien and Riegler, Michael and Halvorsen, P{\r a}l and Niessner, Matthias and Adsumilli, Balu and Bregler, Chris}
}
@inproceedings {28317,
	title = {Reproducibility Companion Paper: Blind Natural Video Quality Prediction via Statistical Temporal Features and Deep Spatial Features},
	journal = {Proceedings of the 29th ACM International Conference on Multimedia (MM {\textquoteright}21)},
	year = {2021},
	pages = {3622{\textendash}3626},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450386517},
	doi = {10.1145/3474085.3477933},
	url = {https://dl.acm.org/doi/10.1145/3474085.3477933},
	author = {Heng Tao {Shen} and Zhuang, Yueting and John R. {Smith} and Yang, Yang and Cesar, Pablo and Metze, Florian and Prabhakaran, Balakrishnan and Korhonen, Jari and Su, Yicheng and You, Junyong and Hicks, Steven and Midoglu, Cise}
}
@inproceedings {28321,
	title = {Reproducibility Companion Paper: Campus3D: A Photogrammetry Point Cloud Benchmark for Outdoor Scene Hierarchical Understanding},
	journal = {Proceedings of the 29th ACM International Conference on Multimedia (MM {\textquoteright}21)},
	year = {2021},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450386517},
	doi = {10.1145/3474085.3477934},
	url = {https://dl.acm.org/doi/10.1145/3474085.3477934},
	author = {Heng Tao {Shen} and Zhuang, Yueting and John R. {Smith} and Yang, Yang and Cesar, Pablo and Metze, Florian and Prabhakaran, Balakrishnan and Liao, Yuqing and Li, Xinke and Tong, Zekun and Zhao, Yabang and Lim, Andrew and Kuang, Zhenzhong and Midoglu, Cise}
}
@article {28007,
	title = {Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events},
	journal = {International Journal of Semantic Computing},
	volume = {15},
	number = {2},
	year = {2021},
	month = {Jan-06-2021},
	pages = {161 - 187},
	publisher = {World Scientific},
	abstract = {Developing systems for the automatic detection of events in video is a task which has gained attention in many areas including sports. More specifically, event detection for soccer videos has been studied widely in the literature. However, there are still a number of shortcomings in the state-of-the-art such as high latency, making it challenging to operate at the live edge. In this paper, we present an algorithm to detect events in soccer videos in real time, using 3D convolutional neural networks. We test our algorithm on three different datasets from SoccerNet, the Swedish Allsvenskan, and the Norwegian Eliteserien. Overall, the results show that we can detect events with high recall, low latency, and accurate time estimation. The trade-off is a slightly lower precision compared to the current state-of-the-art, which has higher latency and performs better when a less accurate time estimation can be accepted. In addition to the presented algorithm, we perform an extensive ablation study on how the different parts of the training pipeline affect the final results.},
	keywords = {3d CNN, classification, Detection, soccer events, spotting},
	issn = {1793-351X},
	doi = {10.1142/S1793351X2140002X},
	url = {https://www.worldscientific.com/doi/abs/10.1142/S1793351X2140002X},
	author = {Olav A. Nerg{\r a}r {Rongved} and Hicks, Steven and Thambawita, Vajira and H{\r a}kon Kvale {Stensland} and Zouganeli, Evi and Johansen, Dag and Midoglu, Cise and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {10.1145/3411276.3412194,
	title = {Mobile Network Performance during the COVID-19 Outbreak from a Testbed Perspective},
	journal = {Proceedings of the 14th International Workshop on Wireless Network Testbeds, Experimental Evaluation \&amp; Characterization},
	year = {2020},
	pages = {110{\textendash}117},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	abstract = {COVID-19 has changed our lives and continues to have a drastic impact. It forces us to impose restrictive social distancing measures and leads us to rely more on the Internet. Mobile networks become one of the major means to access the Internet for most of us. We investigate the performance of 9 mobile networks in Europe around the time when restrictions were imposed, considering web QoE, throughput, RTT, and signal coverage. Our results show countries{\textquoteright} mobile networks are impacted by COVID-19 (as high as 46 \% increase in page load time) at different times based on the outbreak timelines in these countries. Moreover, we find that operators responded properly and the network performance is back to the pre-COVID-19 times.},
	keywords = {COVID-19, mobile network performance, RTT, signal coverage, Throughput, web QoE},
	isbn = {9781450380829},
	doi = {10.1145/3411276.3412194},
	url = {https://doi.org/10.1145/3411276.3412194},
	author = {Rajiullah, Mohammad and Ali Safari {Khatouni} and Midoglu, Cise and Alay, {\"O}zg{\"u} and Brunstrom, Anna and Griwodz, Carsten}
}
@inproceedings {28316,
	title = {Mobile Network Performance during the COVID-19 Outbreak from a Testbed Perspective},
	journal = {MobiCom {\textquoteright}20: The 26th Annual International Conference on Mobile Computing and NetworkingProceedings of the 14th International Workshop on Wireless Network Testbeds, Experimental evaluation \& Characterization},
	year = {2020},
	publisher = {ACM},
	address = {London United KingdomNew York, NY, USA},
	isbn = {9781450380829},
	doi = {10.1145/341127610.1145/3411276.3412194},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3411276https://dl.acm.org/doi/10.1145/3411276.3412194https://dl.acm.org/doi/pdf/10.1145/3411276.3412194},
	author = {Rajiullah, Mohammad and Ali Safari {Khatouni} and Midoglu, Cise and Alay, {\"O}zg{\"u} and Brunstrom, Anna and Griwodz, Carsten}
}
@inproceedings {27700,
	title = {Mobile Network Performance during the COVID-19 Outbreak from a Testbed Perspective},
	journal = {Proceedings of the 14th International Workshop on Wireless Network Testbeds, Experimental evaluation \& Characterization},
	year = {2020},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450380829},
	doi = {10.1145/341127610.1145/3411276.3412194},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3411276https://dl.acm.org/doi/10.1145/3411276.3412194https://dl.acm.org/doi/pdf/10.1145/3411276.3412194},
	author = {Rajiullah, Mohammad and Ali Safari {Khatouni} and Midoglu, Cise and Alay, {\"O}zg{\"u} and Brunstrom, Anna and Griwodz, Carsten}
}
@inproceedings {27698,
	title = {Open Dataset of Operational Mobile Networks},
	journal = {ACM International Symposium on Mobility Management and Wireless Access (MobiWac)},
	year = {2020},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	isbn = {9781450381192},
	author = {ali safari {Khatouni} and trevisan, martino and giardano, d. and Rajiullah, Mohammad and Alfredsson, Stefan and Brunstr{\"o}m, Anna and Midoglu, Cise and Alay, {\"O}zg{\"u}}
}
@article {26426,
	title = {Dissecting the Performance of YouTube Video Streaming in Mobile Networks},
	journal = {International Journal on Network Management},
	volume = {Early View},
	year = {2019},
	pages = {e2058},
	publisher = {Wiley},
	doi = {https://doi.org/10.1002/nem.2058},
	author = {Schwind, Anika and Midoglu, Cise and Alay, {\"O}zg{\"u} and Griwodz, Carsten and Wamser, Florian}
}
@inproceedings {26919,
	title = {Docker-Based Evaluation Framework for Video Streaming QoE in Broadband Networks},
	journal = {ACM International Conference on Multimedia (ACM MM)},
	year = {2019},
	pages = {2288-2291},
	publisher = {ACM},
	isbn = {978-1-4503-6889-6},
	doi = {10.1145/3343031.3350538},
	url = {https://doi.org/10.1145/3343031.3350538},
	author = {Midoglu, Cise and Zabrovskiy, Anatoliy and Alay, {\"O}zg{\"u} and Hoelbling-Inzko, Daniel and Griwodz, Carsten and Timmerer, Christian}
}
@inproceedings {26917,
	title = {Evaluation Framework for Real-Time Adaptive 360-Degree Video Streaming over 5G Networks},
	journal = {S3{\textquoteright}19: Proceedings of the 2019 on Wireless of the Students, by the Students, and for the Students Workshop},
	year = {2019},
	pages = {6-8},
	publisher = {ACM},
	isbn = { 9781450369299},
	doi = { 10.1145/3349621.3355726},
	url = {https://doi.org/10.1145/3349621.3355726},
	author = {Midoglu, Cise and Alay, {\"O}zg{\"u} and Griwodz, Carsten}
}
@misc {26918,
	title = {QoE-Based Analysis of Real-Time Adaptive 360-Degree Video Streaming},
	year = {2019},
	address = {Proceedings of the 2019 on Wireless of the Students, by the Students, and for the Students Workshop, New York, USA},
	isbn = {978-1-4503-6929-9},
	doi = {10.1145/3349621.3355728},
	url = {https://doi.org/10.1145/3349621.3355728},
	author = {Midoglu, Cise and Klausen, Magnus and Alay, {\"O}zg{\"u} and Yazidi, Anis and Haugerud, Harek and Griwodz, Carsten}
}
@article {26036,
	title = {Results from Running an Experiment as a Service Platform for Mobile Broadband Networks in Europe},
	journal = {Elsevier Computer Communications},
	volume = {133},
	year = {2019},
	month = {01/2019},
	pages = {89-101},
	publisher = {Elsevier},
	author = {Mancuso, Vincenzo and Miguel Peon {Quiros} and Midoglu, Cise and moulay, mohamed and comite, Vincenzo and Lutu, Andra and Alay, {\"O}zg{\"u} and Alfredsson, Stefan and rajiulah, mohamed and Brunstr{\"o}m, Anna and mellia, marco and ali safari {Khatouni} and hirsch, thomas}
}
@inproceedings {26037,
	title = {MONROE-Nettest: A Configurable Tool for Dissecting Speed Measurements in Mobile Broadband{\textquotedblright}},
	journal = {IEEE INFOCOM Computer and Networking Experimental Research using Testbeds (CNERT) Workshop},
	year = {2018},
	publisher = {IEEE},
	author = {Midoglu, Cise and Wimmer, Leonhard and Lutu, Andra and Griwodz, Carsten and Alay, {\"O}zg{\"u}}
}
@inproceedings {26038,
	title = {Open Video Datasets over Operational Mobile Networks with MONROE},
	journal = {Multimedia Systems Conference (MMSys)},
	year = {2018},
	publisher = {ACM},
	author = {Midoglu, Cise and moulay, mohamed and Mancuso, Vincenzo and Alay, {\"O}zg{\"u} and Griwodz, Carsten}
}
@inproceedings {26040,
	title = {Visualizing Mobile Coverage from Repetitive Measurements on Defined Trajectories},
	journal = {TMA Workshop on Mobile Network Measurements},
	year = {2018},
	publisher = {IEEE/IFIP},
	author = {Jarvis, Chad and Midoglu, Cise and Lutu, Andra and Alay, {\"O}zg{\"u}}
}
@misc {25623,
	title = {Evaluation of DASH Rate Adaptation Algorithms in Operational Mobile Networks},
	year = {2017},
	month = {06/2017},
	address = {Dublin, Ireland},
	abstract = {In this study, we evaluate the performance of different Dynamic Adaptive Streaming over HTTP (DASH) video rate adaptation algorithms over mobile networks. More specifically, we compare and evaluate the performance of Basic, Segment Aware Rate Adaptation (SARA), and Buffer-Based Rate Adaptation (BBA) rate adaptation algorithms over the 4G-Long Term Evolution (LTE) networks of three Mobile Network Operators (MNOs): Telenor, Telia, and ICE. We use the Measuring Mobile Broadband Networks in Europe (MONROE) testbed\&nbsp;for conducting measurements, and OpenVQ toolbox for evaluation.\&nbsp;},
	author = {Midoglu, Cise and Kousias, Konstantinos and Griwodz, Carsten and Alay, {\"O}zg{\"u}}
}
@inproceedings {25620,
	title = {The Same, Only Different: Contrasting Mobile Operator Behavior from CrowdSourced Dataset},
	journal = {IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2017)},
	year = {2017},
	publisher = {IEEE},
	address = {Montreal, Canada},
	abstract = {Crowdsourcing mobile network performance evaluation is rapidly gaining popularity, with new applications aiming to deliver more accurate and reliable results every day. From the perspective of end-users, these utilities help them estimate the performance of their service provider in terms of throughput, latency and other key performance indicators of the network. In this paper, we build ORCA: Operator Classifier, a Machine Learning (ML) based framework to define and determine the behavior of Mobile Network Operators (MNOs) from crowdsourced datasets. We investigate whether one can differentiate MNOs by using crowdsourced end-to-end network measurements. We consider different performance metrics (e.g. Download (DL)/Upload (UL) data rate, latency, signal strength) and study the impact of them individually but also collectively on differentiating MNOs. We use RTR Open Data, an open dataset of broadband measurements provided by the Austrian Regulatory Authority for Broadcasting and Telecommunications (RTR), to characterize the three major mobile native operators and two virtual operators in Austria. Our results show that ORCA can be used to identify patterns between various mobile systems and disclose their differences from the end-user perspective.},
	author = {Kousias, Konstantinos and Midoglu, Cise and Alay, {\"O}zg{\"u} and Lutu, Andra and Argyriou, Antonios and Riegler, Michael},
	editor = {Kousias, Konstantinos}
}
@inproceedings {25399,
	title = {Speedtest-like Measurements in 3G/4G Networks: the MONROE Experience},
	journal = {29th International Teletraffic Congress (ITC 29)},
	year = {2017},
	publisher = {IEEE},
	doi = {10.23919/ITC.2017.8064353},
	author = {ali safari {Khatouni} and mellia, marco and Marco Ajmone {Marsan} and Alfredsson, Stefan and karlsson, jonas and Brunstr{\"o}m, Anna and Alay, {\"O}zg{\"u} and Lutu, Andra and Midoglu, Cise and Mancuso, Vincenzo},
	editor = {Zinner, Thomas and Aguero, Ramon and Kuladinithi, Koojana and Timm-Giel, Andreas and Ho{\ss}feld, Tobias}
}
@inproceedings {25593,
	title = {Opportunities and challenges of using crowdsourced measurements for mobile network benchmarking a case study on RTR open data},
	journal = {2016 SAI Computing Conference (SAI)2016 SAI Computing Conference (SAI)},
	year = {2016},
	publisher = {IEEE},
	address = {London, United Kingdom},
	doi = {10.1109/SAI.2016.7556101},
	url = {http://ieeexplore.ieee.org/document/7556101/http://xplorestaging.ieee.org/ielx7/7547233/7555953/07556101.pdf?arnumber=7556101},
	author = {Midoglu, Cise and Svoboda, Philipp}
}
@inproceedings {25594,
	title = {Server link load modeling and request scheduling for crowdsourcing-based benchmarking systems},
	journal = {2016 International Wireless Communications and Mobile Computing Conference (IWCMC)2016 International Wireless Communications and Mobile Computing Conference (IWCMC)},
	year = {2016},
	publisher = {IEEE},
	address = {Paphos, Cyprus},
	doi = {10.1109/IWCMC.2016.7577193},
	url = {http://ieeexplore.ieee.org/document/7577193/http://xplorestaging.ieee.org/ielx7/7571053/7577016/07577193.pdf?arnumber=7577193},
	author = {Midoglu, Cise and Wimmer, Leonhard and Svoboda, Philipp}
}
@inproceedings {25595,
	title = {Empirical KPIs for interfered WLAN},
	journal = {2015 International Symposium on Wireless Communication Systems2015 International Symposium on Wireless Communication Systems (ISWCS)},
	year = {2015},
	publisher = {IEEE},
	address = {Brussels, Belgium},
	doi = {10.1109/ISWCS.2015.7454416},
	url = {http://ieeexplore.ieee.org/document/7454416/http://xplorestaging.ieee.org/ielx7/7449547/7454301/07454416.pdf?arnumber=7454416},
	author = {Homayouni, Samira and Midoglu, Cise and Svoboda, Philipp and Rupp, Markus}
}
@inproceedings {25597,
	title = {Measurement setup for automatized baselining of WLAN network performance},
	journal = {2015 International Conference on Systems, Signals and Image Processing (IWSSIP)2015 International Conference on Systems, Signals and Image Processing (IWSSIP)},
	year = {2015},
	publisher = {IEEE},
	address = {London, United Kingdom},
	doi = {10.1109/IWSSIP.2015.7313928},
	url = {http://ieeexplore.ieee.org/document/7313928/http://xplorestaging.ieee.org/ielx7/7301669/7313917/07313928.pdf?arnumber=7313928},
	author = {Berisha, Taulant and Midoglu, Cise and Homayouni, Samira and Svoboda, Philipp and Rupp, Markus}
}
@inproceedings {25596,
	title = {Modeling indoor WLAN performance towards user-oriented evaluation metrics},
	journal = {2015 23rd Telecommunications Forum Telfor (TELFOR)2015 23rd Telecommunications Forum Telfor (TELFOR)},
	year = {2015},
	publisher = {IEEE},
	address = {Belgrade, Serbia},
	doi = {10.1109/TELFOR.2015.7377419},
	url = {http://ieeexplore.ieee.org/document/7377419/http://xplorestaging.ieee.org/ielx7/7368809/7377376/07377419.pdf?arnumber=7377419},
	author = {Midoglu, Cise and Svoboda, Philipp and Rupp, Markus}
}
