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ORCIDSefki Kolozali
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2020 – today
- 2024
[j7]Sefki Kolozali
, Sara L. White, Shane Norris, Maria Fasli, Alastair van Heerden:
Explainable Early Prediction of Gestational Diabetes Biomarkers by Combining Medical Background and Wearable Devices: A Pilot Study With a Cohort Group in South Africa. IEEE J. Biomed. Health Informatics 28(4): 1860-1871 (2024)- 2023
- [j6]Sefki Kolozali, Lia Chatzidiakou, Roderic Jones, Jennifer Kathleen Quint, Frank Kelly, Benjamin Barratt:
Early detection of COPD patients' symptoms with personal environmental sensors: a remote sensing framework using probabilistic latent component analysis with linear dynamic systems. Neural Comput. Appl. 35(23): 17247-17265 (2023) - [c10]Dat Ngo, Lam Pham, Huy Phan, Minh Tran, Delaram Jarchi, Sefki Kolozali:
An Inception-Residual-Based Architecture with Multi-Objective Loss for Detecting Respiratory Anomalies. MMSP 2023: 1-6 - [i4]Dat Ngo, Lam Pham, Huy Phan, Minh Tran, Delaram Jarchi, Sefki Kolozali:
An Inception-Residual-Based Architecture with Multi-Objective Loss for Detecting Respiratory Anomalies. CoRR abs/2303.04104 (2023) - 2022
- [c9]Dat Ngo, Lam Pham, Truong Van Hoang, Sefki Kolozali, Delaram Jarchi:
Audio-Based Deep Learning Frameworks for Detecting COVID-19. EUSIPCO 2022: 1233-1237 - [d1]Sefki Kolozali:
COPD Patient's Symptoms with Personal Environmental Sensors. IEEE DataPort, 2022
- [i3]Eduardo Weber Wächter, Server Kasap, Sefki Kolozali, Xiaojun Zhai, Shoaib Ehsan, Klaus D. McDonald-Maier:
Using Machine Learning for Anomaly Detection on a System-on-Chip under Gamma Radiation. CoRR abs/2201.01588 (2022) - [i2]Dat Ngo, Lam Pham, Truong Van Hoang, Sefki Kolozali, Delaram Jarchi:
Audio-Based Deep Learning Frameworks for Detecting COVID-19. CoRR abs/2202.05626 (2022)
2010 – 2019
- 2019
- [j5]Sefki Kolozali, María Bermúdez-Edo, Nazli FarajiDavar, Payam M. Barnaghi, Feng Gao, Muhammad Intizar Ali, Alessandra Mileo, Marten Fischer, Thorben Iggena, Daniel Kuemper, Ralf Tönjes:
Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams. IEEE Internet Things J. 6(2): 2651-2668 (2019) - [j4]Linda van den Brink, Payam M. Barnaghi, Jeremy Tandy, Ghislain Atemezing, Rob Atkinson, Byron Cochrane, Yasmin Fathy, Raúl García-Castro, Armin Haller, Andreas Harth, Krzysztof Janowicz, Sefki Kolozali, Bart van Leeuwen, Maxime Lefrançois, Joshua Lieberman, Andrea Perego, Danh Le Phuoc, Bill Roberts, Kerry Taylor, Raphaël Troncy:
Best practices for publishing, retrieving, and using spatial data on the web. Semantic Web 10(1): 95-114 (2019) - 2017
- [c8]Alireza Ahrabian, Sefki Kolozali, Shirin Enshaeifar, Clive Cheong Took, Payam M. Barnaghi:
Data analysis as a web service: A case study using IoT sensor data. ICASSP 2017: 6000-6004 - [i1]Nazli FarajiDavar, Sefki Kolozali, Payam M. Barnaghi:
A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams. CoRR abs/1705.09975 (2017) - 2016
- [j3]Dan Puiu, Payam M. Barnaghi, Ralf Toenjes, Daniel Kuemper, Muhammad Intizar Ali, Alessandra Mileo, Josiane Xavier Parreira, Marten Fischer, Sefki Kolozali, Nazli FarajiDavar, Feng Gao, Thorben Iggena, Thu-Le Pham, Cosmin-Septimiu Nechifor, Daniel Puschmann, João Fernandes:
CityPulse: Large Scale Data Analytics Framework for Smart Cities. IEEE Access 4: 1086-1108 (2016) - [j2]Sefki Kolozali, Daniel Puschmann, María Bermúdez-Edo, Payam M. Barnaghi:
On the Effect of Adaptive and Nonadaptive Analysis of Time-Series Sensory Data. IEEE Internet Things J. 3(6): 1084-1098 (2016) - [c7]Nazli FarajiDavar, Sefki Kolozali, Payam M. Barnaghi:
Physical-cyber-social similarity analysis in smart cities. WF-IoT 2016: 484-489 - 2014
- [c6]Sefki Kolozali, María Bermúdez-Edo, Daniel Puschmann, Frieder Ganz, Payam M. Barnaghi:
A Knowledge-Based Approach for Real-Time IoT Data Stream Annotation and Processing. iThings/GreenCom/CPSCom 2014: 215-222 - [c5]Sefki Kolozali, György Fazekas, Mathieu Barthet, Mark B. Sandler:
A Framework for Automatic Ontology Generation Based on Semantic Audio Analysis. Semantic Audio 2014 - [c4]Sefki Kolozali, Tarek Elsaleh, Payam M. Barnaghi:
A Validation Tool for the W3C SSN Ontology based Sensory Semantic Knowledge. TC/SSN@ISWC 2014: 83-88 - 2013
- [j1]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Automatic Ontology Generation for Musical Instruments Based on Audio Analysis. IEEE Trans. Speech Audio Process. 21(10): 2207-2220 (2013) - 2011
- [c3]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Knowledge Representation Issues in Musical Instrument Ontology Design. ISMIR 2011: 465-470 - 2010
- [c2]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Towards the Automatic Generation of a Semantic Web Ontology for Musical Instruments. SAMT 2010: 186-187
2000 – 2009
- 2009
- [c1]Dan Tidhar, György Fazekas, Sefki Kolozali, Mark B. Sandler:
Publishing Music Similarity Features on the Semantic Web. ISMIR 2009: 447-452
Coauthor Index
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